The Internet since its inception, has become a primary source of information flow throughout the world and the social networking has empowered people in every corner of the world to interact, collaborate and share their views online. Among which, the microblogging medium- Twitter, have 316 million active users every month with 500 million tweets posted each day. However, this free medium has lead to lot of consequences which are globally affected. There are countries that follow different religions and rules, but certain tweets and hashtags have created criticism between various countries. Moreover, women are threatened about abuse and violence on Twitter. The rise of social networks have resulted to invade the privacy of people as well. Large amount of public data from twitter is being used by researchers for health and depression monitoring and even for sentiment analysis without the consent of the users.
There are several benefits of Twitter, but it comes with many social and ethical issues that affect people around the globe. Here is an overview of the approaches made by Twitter itself and the Government to censor the contents of Twitter. I have even addressed the issue on how much and what data should be censored so that the people do not accuse the company for its decision to censor any content.
The evolution of social networking comes up with freedom of speech and expression for everyone, but it has many challenges as well as threats to people or entire communities as well. Firstly, the introduction of Twitter censorship can avoid or reduce the criticism faced between countries. Secondly, it can avoid violence and abuse against women. Lastly, it can avoid use of public data without consent of the users.
Twitter censorship can avoid criticism between countries. Twitter is growing throughout the globe. In the year 2012, Twitter posted a blog explaining that each and every country has their different views and it can conflict with views of some other countries. Every country has its own definition of freedom of expression. Some of the countries can have totally opposite views which may not even exist in some other country. Apart from that, other countries may have similar views but their culture may not follow such thing hence creating a conflict between them. For instance, Germany or France are opposed to pro-Nazi tweets. Twitter until now, in case of any conflict, had to delete that particular tweet globally. So they took a decision of censoring the tweets from any user in particular countries with different views. According to this censorship would definitely benefit all the activists. In case if a government demands to get down any tweet which is offending any country, then Twitter has only two options. Either remove that tweet or user in that particular country, or deny the government and getting a risk of blocking entire Twitter for that particular country. So it seems better to get the content blocked for a particular country and still able to reach to rest of the world unlike first when the tweet was deleted entirely and inaccessible to entire world.
Secondly, Twitter censorship can avoid violence threats and abuse against women. By having the right to freedom of expression means that everyone should be openly able to involve and share their views online without having fear of abuse or violence. But it is totally opposite with women on Twitter. In reference to this, Amnesty International conducted an online poll about how women’s feel about and what are their overall experience on Twitter. The results were astonishing as the poll of around 63% to 83% of women stated that they have faced situations threats of harassment and abuse. Meanwhile, the poll of around 78% to 81% women stated that they changed their way of using Twitter as they used it before.
Lastly, Twitter censorship can avoid researchers to use public data without their consent. The amount of user data generation is increasing every single day. Millions of people share their views on tweets daily. People share tweets expressing their opinions or views about almost everything which has created Twitter as a real time information collector. In this generation of data, the analysts or the researchers have started using this public data to analyse sentiment from the opinions [PAPER 12]. Most of the time the sentiments that are analysed are related to politics which may create controversies within or between some countries. Moreover, the data is also used to monitor the health and detect any disease by analysing the behaviour of people. This is possible by noticing the instances of alcohol, cigarettes or hookah and understanding each user’s behaviour [PAPER 6]. Apart from this, researchers are even working to analyse the mental health, i.e the depression at population level [Paper 7]. However, using the data without having the user’s consent is not ethical. Researchers cannot take consent from each and every user, even if he tries to do so, he won’t get reply from half of the users as some of them might have left Twitter or simply ignore the message. Hence, censorship of Twitter can avoid the user data privacy from invading and restrict the researchers to use the public data without consent.
Twitter censorship violates the basic human rights of freedom of speech. The social media companies have reached upto a level where they can determine what crosses their digital borders. So, Twitter has the power to remove or limit the content or entire account of a particular user [https://www.forbes.com/sites/kalevleetaru/2018/01/12/is-twitter-really-censoring-free-speech/#116a59da65f5]. Even the government can involve to remove critical tweets or comments in some cases which stops someone from reaching to the people throughout the globe. If people are stopped to share their opinions about someone or something is violating its freedom of speech. Either Twitter censors some contents in some specific countries or Twitter as a whole is censored by the government, it would definitely violate the human rights.
Twitter censorship grabs more attention to the censored content. A general tendency of citizens have been observed during past few years with respect to censorship. Whenever the government imposes censorship on a content, the people usually tried to acquire that piece of content by learning new methods to evade the censorship. Despite having a traditional perspective that censorship will lead to decrease in access to that content, increasing censorship leads the citizen to invest more in the technology that evades the censored content. Here, the censorship performed as a medium for publicity globally. It shows the same tendency of censorship that by having blocked the most popular social networking platform Instagram in China has led millions of people to evade the Great Firewall and try to access Instagram. So in this case, the situation suddenly increased the number of visitors from China who were trying to access Instagram’s website. is evident to this scenario stating that the Chinese users that never showed interest to Instagram ever started to get into topics of some occurring protests online just after Instagram’s service was stopped in China.
Although there may be some good benefits of Twitter as a microblogging platform and its censorship may violate the basic human rights of freedom of speech and grab more attention to the censored information. However, there are various social and ethical implications of Twitter. The social controversies on Twitter have a negative impact between countries and creates criticism between them which may indirectly hurt their religion or their way of living. Moreover, it causes silent abuse and violence threats to the women who wants to get involve and give their views and opinions, which may demotivate women from raising their voice. Everyone should be treated equally and women should not be criticised for their thoughts. Apart from this, the public’s opinions or views and every other tweets from the Twitter is being used by the researchers to do sentiment analysis, that too without the consent of the users which is ethically wrong. Hence, in my perspective, Twitter should be censored for the betterment of the society and avoid the criticism and silent abuse.
Twitter is an online microblogging site/social network where users can instantly compose and share messages, called “tweets”, in 280 characters or less. Twitter was founded in 2006 by Jack Dorsey, Noah Glass, Biz Stone, and Evan Williams (Skemp, 2019). On Twitter, each user has a profile that can be viewed and followed by anyone if their profile is public, users also have the option of making their profile private and only those approved can follow and view their content. One big feature Twitter is known for is hashtags, which, with the use of the “#” symbol followed by any word, allows users to connect and talk about a specific thing. Twitter also features, “Trending Topics” which highlight current topics of discussion and popular hashtags (Skemp). As of 2018, Twitter has around 321 million active users (Twitter, Inc, 2019). Twitter allows for users to connect with celebrities, musicians, politicians, and companies. Some of the most notable users of Twitter include Chrissy Teigen, Ariana Grande, Barack Obama, and Donald Trump.
One major benefit for users of Twitter is the ability to connect and engage with other users from all over the world at once. Users can talk to each other about the latest episode of their favorite show, discuss a presidential debate, or even share updates on an emergency within seconds. Users are also able to receive the latest information regarding breaking news stories much faster than traditional media outlets. Twitter also provides an outlet for users to share their talents such as singing, dancing, writing, and so much more.
Twitter makes money from advertising, promoted accounts and trends, and data licensing. About 86% of Twitter’s revenue is from advertisements (Beers, 2018). In 2010, Twitter began to offer companies the ability to purchase “promoted tweets” which allow for certain tweets to appear in search results or on a user’s timeline if the product is relevant to the user. In 2016, Twitter launched the “Instant Unlock Card” which is promoted content that features a button usually stating if you click it, you will tweet about a brand and instantly unlock some type of reward, usually exclusive content that can only be unlocked if you tweet about a brand (Twitter, 2019). Twitter’s ads and promoted tweets are personalized to each user, and if users do not wish to see certain ads, they are able to hide the ad. If you are a brand or company, you can reach specific demographics to ensure your ads reach people who are likely to buy your product.
Twitter allows for brands and companies to engage with consumers in an authentic way. The website allows for brands to share information about their latest product, answer questions, or take part in playful banter with consumers or even other brands. Taco Bell, Wendy’s, Apple, and Netflix are popular users on Twitter because of their creative, fun, and engaging tweets. On Twitter, a brand/company can also search their name and see what users are saying about their company and take ideas or criticism into consideration. For example, Amazon does not have a live chat on their website, but they do have a Twitter account specifically to help consumers with any issues they may have. Another benefit is, with the use of hashtags, a brand/company can instantly create a campaign to gain attention and potentially trend on Twitter. About any industry can thrive on Twitter if they use it to their full advantage, because even though the use of Twitter does not automatically mean an increase in sales, it does get a product into consumers heads. When consumers decide to buy or use a specific brand, they will have the idea of the one they see being advertised or engaging with users on Twitter.
Two successful campaigns through Twitter include Always’ “#LikeAGirl” campaign and Nike’s #Breaking2 campaign. In 2014, the feminine hygiene products brand, Always, uploaded the “Like a Girl” social experiment video on their YouTube channel and thus launched the “#LikeAGirl” campaign. The first half of the video featured many different people acting out actions such as running, throwing, or fighting “like a girl.” These actions were initially acted out in a silly or weak way. The second half of the video featured young girls who were asked to perform the same actions “like a girl.” Rather than perform the actions in a weak way, the young girls performed the actions to their best ability without holding anything back. At the end of the video, girls (and boys) were encouraged to use the hashtag #LikeAGirl to share the incredible things they or other women do (Always, 2014). According to Always, “the program garnered more than 290 million social impressions and 133 thousand social mentions with #LikeAGirl (99% positive/neutral) in the US alone.” In addition, the campaign also managed to increase Always Twitter followers by 195.3%.
In 2017, Nike decided to use Twitter’s live video feature powered by Periscope by streaming their attempt at breaking the world marathon record. Nike teamed up with three marathon runners, Lelisa Desisa, Eliud Kipchoge, and Zersanay Tadese and they had to run 42 kilometers in less than 2 hours to break the record. The hashtag used for the event was #Breaking2. In order to be notified of the event the second it started to stream, all users had to do was like or retweet the #Breaking2 tweet put out by Nike. Through Twitter, users were able to watch the live stream and chat with other users watching the event. While the record was not technically broken, the event became Twitter’s biggest-ever brand-driven, live-streaming event (Natividad, 2017).
Because Twitter allows for messages to be sent out to an audience immediately, you run the risk of damaging your credibility if you were to send out misinformation, because once it is posted then it gets shared, screenshotted, and talked about. Another issue is many brands on Twitter try to appeal to audiences by tweeting relatable or funny tweets. This can be a hit or miss for any brand. Sometimes they come off as cringeworthy or even insensitive and suddenly a brand finds themselves dealing with damage control. User error in general is the biggest risk with using Twitter. You must be mindful of what you like or retweet or even who or what you respond to.
In 2012, a hashtag intending to promote Susan Boyle’s album release trended for all the wrong reasons. The hashtag, which was meant to be read as #SusanAlbumParty, was seen as #susanalbumparty and Twitter users instantly made a mockery of the hashtag because of the alternative words that could be picked out within the phrase. The original tweet was deleted and changed to #SusanBoylesAlbumParty, but the damage was done, and the internet was not going to let Susan Boyle’s PR team forget it. Multiple memes and trolling ensued seconds after the hashtag was used, and rather than a celebration, the entire campaign was used to mock Susan Boyle and her PR teams flub (Kolowich, 2017).
In 2014, the hashtag #myNYPD was tweeted out by the New York Police Department news twitter account. The hashtag was meant for users to share positive images of citizens with members of the New York Police Department. However, Twitter users used the hashtag to share images of police brutality instead (Oh, 2014). The New York Police Department did not take into consideration just how quickly social media can turn something seemingly positive against you.
These two examples show that the use of the hashtag must be viewed from all angles. The Susan Boyle incident was a poor word choice and lack of capitalization and the NYPD did not consider how trolls could hijack the hashtag and use it against them.
I recommend the use of Twitter for any brand or company’s social media efforts. Twitter allows for consumers to connect to a brand or company instantly with questions, comments, or concerns. The site has many different options for a company to promote themselves in order to reach a wide or specific audience. And finally, Twitter brings more visibility to your company. Your company will show up in more search results and if you have successful interactions with users, people will talk about your company more and share the interaction on other social media platforms.
Twitter, a microblogging service that allows subscribers to send “tweets” of 140 characters or less to their followers is a giant technology company that started in 2007 by founder Evan Williams. Twitter can be accessed through its website, SMS, or mobile device and has multiple features such as pinning tweets, advanced search, tags, and alerts, that made Twitter a widely regarded company to have social and political influence as it enables its users to access and spread news faster than ever- been used as a media platform and communication tool for the Iranian revelation, the Arab Spring revolutions, and entertainment events to name a few-. Despite the optimistic attitudes of its entrepreneurs, the enormous amount of investment it receives (from 2009 to 2011: 1.25 billion dollars), and the high evaluation it has on the New York Stock Exchange Market (In 2014 the company valued at 26.63 billion dollars), Twitter is challenged to generate revenues from declining advertising prices, increase its customer base, and recover its operational costs to make the company profitable.
Business Model Canvas:
1- Customer segments:
Twitter has a self-service ad platform that allows small business owners to advertise through Twitter. Large Corporation Such As Starbucks are also using Twitter advertising services. Moreover, data licensing counts for fifteen percent of the company business. These customers include analytics firms, which analyze the data to identify consumer trends; news agencies, which filter the data for breaking news stories; and even high-frequency trading firms, which use trending tickers and stories to place trades. Twitter sells its river of information to companies that try to turn its tweets into actionable data. Lastly, users that use Twitter to interact with friends and family and watch their celebrity feeds who are regular customers and constitute the bulk of its customers segments.
2- Value proposition:
Twitter delivers real-time information, empowerment, and engagement that stimulate innovation and idea exchange. These tweets also have a set of embedded metadata such as location, time and topic. Furthermore, users can also aggregate their messages by using the hash-tag keyword that triggers access to all tweets with that particular hashtag. This drives a sense of community, affinity and collaboration.
User Benefits – Users share content with the world, get real-time and relevant content in return and also get to participate in conversations with people through tweets or messages.
Advertiser Benefits – Viral global reach, unique ad formats, real-time connection with the audience.
Data Partner Benefits – Access, search and analyze data and generate insights to monetize.
3- Channels:
Customers can access Twitter through the following options; Websites, Desktop apps, mobile aps, SMS, and Twitter API.
4- Customer relationships:
Twitter provides additional support for customers who want to optimize the server for their business by attracting specific target segments that most relate to their product or service. The partner program links a customer to ad partners that have enterprise tools and expertise to help create and manage high-quality ads with advanced features and capabilities. Another option for customers is using the data partners that would help make well-informed decisions, study past behaviors to predict future trends and to engage most valuable audience. In addition, regular users have a direct communication line with the Twitter app and website, it was described that the app and the website to operate as a self-taught website or an app that customers find easy to comprehend and use.
5- Revenue streams:
There are two main revenue streams for Twitter: A) Advertising: There are three main ways for a company or an individual to advertise o n Twitter: by promoting a tweet that will appear in people’s timelines, promoting a whole account, or promoting a trend. B) Data licensing: The micro-blogger sells something known as the ‘firehose’, its public data, which often adds up to about 500 million tweets each day. Companies can dive deep into the data to analyze consumer trends and sell their insight to other brands and companies.
6- Key resources:
The platform of Twitter is perhaps the most crucial resource as it has. As twitter would use the service to build and expand its customer base. Specifically, the network allows connectivity and communication between people that would not have otherwise would be connected without twitter. The technological advancement that Twitter launches and updates is also a crucial resource for the network, as it helps the network compete in the digital social media circle.
7- Key activities:
Since Twitter’s major resources are its platform and technological advancement; key activities include maintenance and the development of these resources. It can be summarized as website and app development and maintenance. Another activity is the maintenance of user data for that Twitter stores, analyzes, shares, and uses Big Data from its platform.
8- Key partnerships:
a) Search Vendors: Twitter licenses full feed of public tweets to search engine vendors such as Microsoft (Bing Social), Google (Google Realtime), and Yahoo. This helps in enabling real-time search and discovery.
b) Device Vendors: Twitter partnered with Apple to enable deep integration of Twitter in iOS5 mobile operating system for iPad, iPhone, and iPod touch. This means users can tweet directly from Apple apps such as Camera, Photos, and Safari, along with third-party apps such as Flipboard, Livingsocial, and Instagram.
c) Media: Twitter has entered into partnerships with companies such as Mass Relevance and Crimson Hexagon to help media companies and brands deliver compelling Twitter integration to their users more easily. This can help media companies capture real-time reactions to the important news. Though these partnerships are not major source of revenue, they help in expanding user base. Additional visibility drives further growth for Twitter.
d) Mobile operators: Twitter has partnered with Telecom operators across the globe to enable users to send and receive tweets from mobile phones using SMS.
9- Cost structure:
A) General and administrative
B) Sales and marketing
C) Research and development
D) Cost of sales or Revenues
Empathy map for Twitter main customer’s base:
Think & Feel: I feel connected “ my friend favored my tweet. Excited knowing a favorite artist coming to my city. Worried, saw sad news somewhere in the world. Think about the content being shared.
See an ad of Starbucks, Lyft, or Whole Foods among others. News Channel Account tweet about war in Yemen, and to promote one’s own tweet., and a list of Trending Hash-tag worldwide or one’s country.
Hear: Follow me on Twitter, from friends or public figures on other social media accounts. Follow us on Twitter from other businesses that you just visited their business or purchased a product or a service from. You didn’t hear about it? It’s trending on Twitter from a friend or coworker.
Say or Do: Retweets, favorite, create a hash-tag, tweet negatively about a company, service, or a person while tagging them, and share a meme or a link to a video.
Pain: So much to be updated about, and so many opinions, might feel attacked or afraid to share your own opinion.
Gain: Feel connected to friends. Feeling up to date with world news.
Business Model Patterns:
Twitter uses a multisided platform that it serves multiple distinct but interdependent groups of customers such as data licensing companies, business owners, and regular customers who use the network to communicate with friends, family, and public figures. The strengths of Twitter’s current business model is first their use of technology to create and maintain meaningful relationships within its customer segments, whether it’s a regular customer to another regular customer relationship, or business to regular customer relationship, it creates immediate value to all their customer segments. A second strength of Twitter is the ability for users to target their message to a specific audience, this can be done through the hashtag feature that focuses on a topic or based on other elements such as location. Third, Twitter customers can use Twitter as a marketing tool to advertise and communicate with their own business customers free of charge, which untimely expands Twitter’s customer base
A shortcoming of Twitter’s business model is one linked to their user data and privacy. Customer data is one of the most crucial parts of Twitter’s business data, for that Twitter shares Big Data with third parties for analytics purposes such as better-targeted advertising efforts and promotions. However, customers of Twitter would also share information about what they are doing, their location, what music they are listening to, and products they have been purchasing, among many of personal information that puts a risk of customers being spammed. Another shortcoming of Twitter’s current business model is that there is no solid revenue model – Being ad-free to a lot of small businesses that can use the platform to post their product features, pictures, or videos with no subscription fee. Even though Twitter does charge companies for advertising and promotion, it fails to charge the small businesses for utilizing the platform free of charge. Twitter is initially employing the traditional Cost Per Mile (CPM) model, which involves an advertiser paying for their advertisement on a per-view basis, so it would cost X per one thousand views.
Alternative business model:
An alternative or a modification to the business model would address a previous shortcoming of Twitter’s current business model, which is the limitation of revenue on its current advertising strategy. Instead, they can offer a service that is described as ‘resonance’. Resonance is a system that incorporates how many times a tweet is viewed, retweeted, replied to or added as a favorite and in turn assigns it a score. If a user is not interested in a link they simply do what they have always been doing and ignore it. If the resonance score for a tweet is low, it will be dropped from the system and the advertiser will cease to be charged. This in principle seems to be a system, which will work well for all parties concerned, the user is not bothered with the ad and the advertiser can rethink their strategy without wasting further money.
In addition, Twitter can implement a feature where customers can link their credit card to their Twitter account to purchase within Twitter from the advertising shown on Twitter, where it can take a transaction fee from the company where the item was purchased. These modifications are stronger than the current model because it would allow Twitter to utilize their full offered features such as the number of retweets an advertising tweet would get or a “favorite”, it eliminates customers who might not be fully interested in the add or they might not have seen it. Simply, it helps to advertise to precisely define t and interact with their target market. Moreover, the ease of payment within Twitter means that customers can easily make a purchase without the pain of entering card information. The reason why I think these modifications would work for Twitter is that it creates value for two of its customer segments, first, advertisers would have a more efficient way to seek customers that demonstrate involvement with their ads by “retweeting” or “favoring”. Customers who would like to make a purchase through a Twitter ad would find no hassle in doing so, as their credit card information would be linked to their account in case there are interested in making a purchase. These modifications can boost Twitter’s revenue simply for these reasons, ease of payment to customers, and advertisers can reach involved customers that are more likely to purchase their offer.
The Story:
” We share a desire to be heard, seen, and understood in a world that is fast changing and where news is flashing by by the second. Here at Twitter, we stand by the people, through the Iranian revelation, the Arab spring, or through an Oscar selfie, or even to help you by selling more of these delicious cupcakes, we hear you, we see you, and we can spread your news. With Twitter, you are the story; let Twitter be your medium because Twitter enables you to share your ideas, emotions, and creativity faster and louder. Twitter now allows you to share your news to the most involved customers, with Twitter you can purchase what you like immediately, and at the same time enjoy a giggle at your friend’s tweeted meme. Be part of the murmuration.”
Business Model Environment Assessment:
Key Trends: Increase in popularity of social media usage globally (with 3.196 billion users worldwide in 2018, up to 13% increase from 2017),. Growth of social TV: video content. Customer trust declined, and peer influence rose.
Market Forces: Evolving customer expectation. The emerge of hybrid cloud IT infrastructure to reduce cost of operation Big Data and increasing demand for content security.
Macro-Economic Forces: The emerge of E-commerce markets, market globalization, Social Network continuous technological innovations.
Industry Forces: Low entry barriers, a large pool of competitors such as Facebook, YouTube, Instagram. Substitutes to social media networks are moderate, as each network would try to come up with new and innovative to its customers. Visitors constitute the main supplier to social networking sites and apps, whereas advertising companies are the largest buyers.
SWOT Analysis For Revenue Streams/Twitter:
The strength of Twitter’s revenue streams is its diversity where it can generate revenue from both data licensing companies as well as advertisers. A weakness, however, is that those revenues are challenged to make a profit with its current strategy as customers’ usage of the network are declining. An opportunity for Twitter is one regards the additional revenue it might generate if it can charge for Twitter promotion influenced transaction, it can also boost its customer base if it adds and succeed with the addition and collaboration of video content creators with their new partnerships. The threat to Twitter’s revenue stream is internal because balancing their cost infrastructure while stimulating customer involvement through technological innovation such as automated credit payment and content creation has been historically challenging for Twitter. They are known for the instantaneous nature of exchanging information; the expectation would be high from its customers to remain in speed with its current offerings as well as the new ones.
Other Consideration/Expanding on value proposition:
As discussed previously Twitter’s main challenge is to generate profit from its current business model, the main reasons are a declining price for advertisements and fewer customers using the network. Twitter can expand the value it offers to its customers: immediate credit payment and more specified targeting tools for advertisers are two modifications that can enhance the business model. Twitter can increase its value to its customers in several ways if they better understand the different and evolving needs of its customers, such as do they want larger tweet space beyond the 140 characteristics. Or do they want the ability to add short voice notes for advertisers to communicate better within their tweet space? The theme is to provide more of the current features in a simple way that satisfies all needs of their customer base.
Executive Summary:
Twitter offers its multi-customer segment a platform where people can enjoy and be part of a network that delivers real-time information, empowerment, and engagement that stimulate innovation and idea exchange. Their use of technology helps create and maintain meaningful relationships within its customer segments that make Twitter the powerful social network it is today. However, Twitter has struggled to generate a profit and its current business model shows little guidance in how to make the giant company profitable in the long run. One of the main issues the report aims to address is its revenue streams as it seems to be shrinking due to decreasing customer base participation and the fall of its advertising prices. In my report I have discussed a modification to Twitter’s business model where it focuses on two suggested ideas: 1) To offer its advertisers the resonance model to advertise that depends on customer involvement, it is a system that incorporates how many times a tweet is viewed, retweeted, replied to or added as a favorite and in turn assigns it a score. 2) Offer its other customer segments to link their credit card information to their Twitter account to ease the purchase process and so that Twitter can profit from taking a transaction fee from the company it helped to promote their product or service. Both of these ideas aim to add value to Twitter’s customer segment that can help boost its probability.
Nowadays text mining and sentiment analysis are sensational topics in the area of research. Twitter, a social media website which allows different ways of demonstration opinions and establish communication among the users, all over the world. Since Twitter is very distinctive so it’s difficult to assemble data for sentiment classification. , data is first preprocessed before analysis, to enhance the tweet. After tweets are processed, different information and features are produced from them.[1]
Twitter, a social networking service where users can post and communicate with messages basically called “Tweets’ in its terminology. ,but only registered users can share their views in the form of likes, comments , posts , retweets and unregistered users can just read them . Twitter was called into existence in March 2006 by Jack Dorsey , Biz Stone, Noah Glass and Evan Williams and instigated in identical year July. Earlier, more than 120 million users posted 400 million tweets per day, and besides service touched a standard of 2 billion search questions everyday.[2]
Twitter Sentimental Analysis focuses on the mood during which the user posted the tweet. It tells the polarity of text, categorizes the tweet into three branches of expression that are positive,negative or neutral. For analysis tweet must be limited under 140 characters. User needs to convey their message within the character limit. There are a large number of tweets in a day there are a large amount of tweets posted by users because there are a large number of users on this platform so it becomes difficult to analyse what type of tweet was posted by the user. In this project Twitter Sentimental Analysis, we will categorize the tweets which are positive, negative or neutral. The primary task in sentiment analysis is to classify the polarity of a given text at the document, sentence. Advanced sentiment classification looks for emotional states such as whether the sentence shows ‘angry’, ‘sad’, or ‘happy’ emotion of the user.
Currently there are three main approaches for sentiment analysis which are statistical methods, hybrid approaches, and knowledge based approaches.[3]
For this technique Text mining and sentimental analysis are used they are used to analyze unstructured tweet text to get positive and negative polarity about this text. Also, tweet frequency analysis is done to view the changing trend in public opinion across a time interval of 9 days’ tweet text data. It is found that a large number of people have this attitude towards this incident by using 2-3 hashtag with overall data.
So why is Twitter Sentimental analysis important?
It helps to Analyze thousands of tweets which are mentioning your brand or your business. Also used for real time analysis: It is also used to monitor Twitter sentiment analysis is essential to observe sudden shifts in customer moods, detecting if complaints are increasing, and for taking action accordingly. With sentiment analysis, you can also monitor brand mentions and gain actionable insights.[4].
One important step in sentiment analysis is preparing the dataset because the language that is generally used in the tweets is not a level language, it is mostly some short forms or some fancy words . Most of the times the spelling or the utilization of the words used may vary a lot from people to people. As it is a superintended learning technique, so it requires a training set to tell the polarity of the text. Data Preprocessing becomes very necessary because of the use of patter, URL removal and mis spelled words. To solve decipher problems because of patter words, a dictionary is retained, which analyses the words and after that returns the word with its similar or identical meaning.
SENTIMENT CATEGORIZATION – Classification is done after performing above steps using the machine learning algorithm which is Naive Bayes, It Keeps Up Vector Machine, Maximum Entropy and Troupe Classifiers. Categorization Techniques Normally, there are a different kind of classifier required for categorization of text in twitter analysis. Naive Bayes Classifier The algorithm in the naive Bayes classifier requires all characteristics of the feature vector. It tells the conditional probability. Sentiment Analysis can be done so productively on Twitter because of the existence of predefined properties like emotional keyword, a number of positive and negative hashtag, the number of keywords which are positive or negative; it also observes the emotional keyword used and emojis used. The relationship existing between the characteristics is not regarded in this classifier for categorization. [5]
References
Nagamanjula, R., & Pethalakshmi, A. (2020). A novel framework based on bi-objective optimization and LAN2FIS for Twitter sentiment analysis. Social Network Analysis and Mining, 10(1). doi:10.1007/s13278-020-00648-5
Wikipedia contributors. (2020, October 26). Sentiment analysis. Retrieved November 6, 2020, from Wikipedia, The Free Encyclopedia website: https://en.wikipedia.org/w/index.php?title=Sentiment_analysis&oldid=985616558
Mishra, P. (2020). Twitter Sentimental Analysis. International Journal for Research in Applied Science and Engineering Technology, 8(5), 2476–2478.
Karumanchi, B. (2020). An unsupervised clustering approach for twitter sentimental analysis: A case study for George Floyd incident. International Journal of Computer Trends and Technology, 68(6), 46–50.
Singh, S. S., Dwarakanath, D., Santhoshini, & Mary, J. (2020). Twitter Sentimental Analysis. Journal of Advanced Research in Dynamical and Control Systems, 12(05-SPECIAL), 868–873.
Twitter application programming interface (API) is a publicly available extension of Twitter that allows programmers to incorporate various aspects of the social network into their applications, websites, and software. This literature review examines research about the API and about its usage on a number of problems.
The highlighted examples include the usage of the API in gathering data for administration, medical, and scientific usage. As part of the review, the discussion also shows the limitations that come with relying on the Twitter API and the variations that exist with the different APIs, as well as the possible motivations for using them.
The most common usage is the collection of Geo-location data to link content with geographical location for the sake of explaining a given issue. The review also mentions the architecture of Twitter as a system that gets better with additional usage and uses this view as a basis for understanding how seemingly independent uses of APIs contribute to the overall usefulness of the social network.
Literature review
Twitter is an excellent social media tool for individual and group usage, both from the perspective of the information consumer and the creator. However, in addition to its basic architecture as a social network, it is also a very credible tool for gathering crowd-sourced information.
Twitter can offer location data, such as Global Positioning System (GPS) coordinates. Such information is useful for studying and monitoring online health information (Burton, Tanner, Giraud-Carrier, West, & Barnes, 2012). Understanding the location information is not as widespread as the use of Twitter itself.
Part of the reason for the limited usage is the inadequate amount of documentation and research on the subject of Geo-location using Twitter and mining of online health information using Twitter (Burton et al., 2012). Twitter works well for information researchers because it is a collection of information bread crumbs.
People’s interaction online leaves tiny records of their daily experiences (Burton et al., 2012). With traditional behavioral assessments, one would have to go for self-report or observation as methods of research. However, with the proliferation of mobile communication devices, all that is easy using different tools.
With social media apps that link to social media networks, it is both easy and possible to do real-time data collection and study behaviors and health outcomes (Burton et al., 2012). Research by Burton et al. (2012) used Twitter streaming application-programing interface (API) to observe tweets for 2 weeks.
The researchers found out that the parsed state data for the United States, collected using the Twitter API, matched GPS-derived state data 87.69% of the time. This shows the potential of the tool as a viable data collection method for seeking behavioral and self-reported data (Burton et al., 2012).
According to Fitz-Gerald (2010), creative uses of the API available using the platform include science, religion, marketing, social change, money matters, and education. Others are sports and entertainment. With proper adjustment, the API can suit any area of interest in life.
Many uses of the API are indirect, as users interact mostly with already developed applications that employ the Twitter protocol. Thus, research into the usage of the API can as well focus on the applications presented for search, publishing, information streams, and statistics based on the social network.
Being familiar with the elements of web programs is important for anyone looking into the exploration of the Twitter API as a tool. Otherwise, one has to use already developed applications for end users. Key programming elements required include CSS, PHP, and MySQL.
They are the software building blocks. Fitz-Gerald (2010) explains the process of setting up and managing API and the automation process that completes the endeavor. The technical aspects of the tool make it less friendly for ordinary usage and explain why its usage is not very popular, despite a large amount of publicity.
Benhardus and Kalita (2013) researched on Twitter’s ability to show trends on social matters around the globe. They realized that it is a useful tool for examining various aspects of natural language processing (NLP) and machine learning. On Twitter, a topic is usually a persisted collective chatter that is user-initiated.
The topics of discussion or conversation are usually responses to events. When there is a sudden high intensity, it becomes a spike. Trending topics, on the other hand, are combinations of spikes and chatters, but they are mainly characterized by chatter.
This is where many people are speaking about the same thing, but not necessarily reacting to an event. Some challenges for researchers would be to first define the trending topic and to determine what would constitute a certain success rate for the methodology used. Sometimes, when using Twitter’s data, it is useful to have different methodologies for the sake of cross-referencing of data (Benhardus & Kalita, 2013).
The research by Benhardus and Kalita (2013) examined the terms used on Twitter and their potential to match trending topics. The aim was to find out the methodologies most useful in predicting trending topics. The tested ones include normalized term frequency analysis.
In their conclusion, the research explained that future research and applications can look into the relationship in the method, the term, and the trending topic on Twitter and on other sources as search engine trends. Mills (2011) builds on the theory of concretization of technological objects and applies the advanced theory to the area of software studies.
In discussing examples of applications, the researcher looks at the financial markets and Twitter APIs. According to the original theory examined, the joining of two technologies to work as one equipment or system creates a series of problems that will need resolving.
The solving of the problems becomes concretization, or sealing the visible differences in the two technologies. The theory also insists that concretization takes place independent of economic and social concerns and cannot become simply an anterior scientific principle.
The best systems are the ones that get better when more people use them, because usage increases the resolution of the existing problems. Networked systems or networked features in a system are examples examined by Mills (2011). Twitter is an example of an open invented technical individual (ITI), where the creation of a sub-system results in a milieu that needs management and maintenance.
Twitter users operate in a global sphere, but they remain hidden in their limited focus on specific topics and may not be aware of what is going on elsewhere in the platform. Their awareness emerges when they take part in regional or global events through Twitter, such as the FIFA World Cup or the Arab Spring. The streams of tweets are individualized and they resemble separate life forms.
Users edit stream membership to modulate the amount of information flow and character that goes to their personal Twitter milieu (Mills, 2011). Access to Twitter steams using different software further individualizes user experiences. Here Twitter API plays an important role in developing third-party software.
The three components useful for development are REST API, Search API, and Streaming API, which can be used individually or collectively. The first API is just for sending and receiving tweets or un-following or following users. When used, it lets software mimic the functions, just like Twitter.
The search API is for allowing access to trending data, while the last one is for allowing software to access and publish content from the dynamic milieu of Tweets available at the time on the social network (Mills, 2011). Although the applications of Twitter are numerous, the basic construction of tweets and identification of tweets makes it possible for maintenance and management of the milieu of Twitter.
In all cases, there will be id, text, source, screen name, location, and follows count for every tweet or profile (Mills, 2011). Field and O’Brien (2010) explain how search tools incorporating geographical information are useful for location-based software. If the subject examined is the interaction of people around specific topics, then the Twitter Search API comes in handy.
Its incorporation into the ArcGIS flex viewer software, as an example, allows users to search for tweets in a limited geographic area. Unfortunately, the Geo-location option on Twitter is not mandatory for users. Thus, for researchers, the collection of location data or the limiting of data range based on location can be hampered by the provision (Field & O’ Brien, 2010).
The combination of the search API and cartography, as well as web design allows practitioners to come up with websites that present visual rich maps that show common threads and can connote activity emanating from a location based event and relate to discussions about the event taking place outside its geographic location (Field & O’ Brien, 2010).
In fact, the usage of Twitter API is prevalent in politics and administration. The social network and participation by many users makes it a good place for authorities to find information that can help in policy formulation, law enforcement, and voting. In the UK, the London riots triggered police officials to use Twitter to get moment-to-moment updates and to reassure the public (van de Velde, Meijer, & Homburg, 2014).
Examining trends or streams on Twitter must be done with caution. Not all tweets appearing in a person’s timeline are actually read by all followers. However, so far, there is no possibility of noticing what a person reads and does not read.
Thus, much of the data collected or the information is an assumption. However, there is a high chance of people reading tweets about a trending topic because the subject is the matter of discussion for more than one Twitter account on a user’s timeline (van de Velde, Meijer, & Homburg, 2014).
Retweets can show that a user read a message, thereby serving as the most credible form of acknowledging receipt of a tweet. However, it is important to separate retweets from the original messenger and those from the readers. The original messenger can retweet the original message that comes as a reply, which means it has an additional component attached by the user replying.
Thus, it is possible to tell why a tweet is retweeted many times and why others are not. Social parameters such as the authority of the positing account and the profiles mentioned in the tweet can play a part. User specific characteristics like audience size, time of tweeting, and topics discussed, as well as the elements included and the provisions of interactivity contribute to the overall discussion level that a tweet is able to garner (van de Velde, Meijer, & Homburg, 2014).
Researchers are increasingly turning to Twitter to examine various social aspects and their relationships with other non-social parameters. For example, researchers can look at the effect of weather on people’s moods by going after the emotions expressed on Twitter. The streaming API offers a free 1% of tweets (Morstatter, Pfeffer, Liu, & Carley, 2013).
Researchers only need to put in the right parameters to get the data required. Unfortunately, when the volume of a query exceeds the 1% of tweets, then the response given to the examiner is a sample. There is no way to know the criteria of sampling other than to contact Twitter. Presently, the methodology of sampling remains a secret (Morstatter et al., 2013).
The emerging problem of relying on the streaming API for collecting data is the bias that is present with the sampling. Researchers need to undertake additional steps in their methodologies to vet their data sets using the firehorse methodology (Morstatter et al., 2013).
Unfortunately, Firehorse data is costly. As an alternative, researchers can use the sample API to cross check the data sets obtained by the streaming API. The sample API presents a true report of what is happening on Twitter. When time periods are used, it is possible to tell biasness in the streaming API data and eliminate it before processing the datasets for analysis in research (Morstatter et al., 2013).
Twitter is not the first web service that provides an API that allows users to mine data. However, it is among the most popular ones. Others include Google and Facebook APIs. The APIs allow users to integrate various features into their websites (Aboukhalil, 2013).
Now that social networks like Twitter are common as mobile device applications, they have become inseparable from social researchers. They are useful for information gathering and their exploitation is subject to the capabilities presented in the software used for mining the data (Oussalah, Bhat, Challis, & Schnier, 2013).
Technology demand for collection and mining of Twitter content is increasing, as more users use the platform to create or share content. The challenges of designing the right software that can fulfill the increasing needs of the public mainly relate to the semantic aspect of information on Twitter.
In addition, all software seeking to build their functionality on top of Twitter is restricted to rely on available Twitter API only to generate information and reports. Thus, dependency on the available APIs is also a limitation (Oussalah et al., 2013).
There are several architectures for software suggested by researchers, describing the best way to build on the capabilities of the Twitter API and limit exposure to its shortcomings at the same time. For example, there are suggestions to use product-class software framework or the infrastructure component to have software that allows users to search and link to Twitter friends and followers (Oussalah et al., 2013).
However, the building of the software requires developers to have the right knowledge for handling the basic components of Twitter API appropriately. Just as end users are limited in their use of APIs due to the lack of programing knowledge, developers must also possess the right techniques and understand design.
Moreover, they need adequate comprehension of end user intentions before embarking on the development of a software solution (Oussalah et al., 2013). An example comes from research by Ekins, Clark and Williams (2012) that reviewed a chemistry mobile app for collaboration created by Open Drugs Discovery Teams (ODDT) project.
In the past, most of collaboration tools for medical discovery hinged on the desktop computer. The computers have also been mostly restricted to laboratory facilities and special research units. However, Ekins, Clark and Williams (2012) contend that there is an emergence of mobile apps used in general practice and in the drug discovery initiatives.
Cloud computing and its provision of software as a service have enabled researchers and scientists to access software that requires powerful computing resources. However, instead of using desktop computers that are powerful, they are using mobile phones that provide adequate access to the cloud interface and useful input options for manipulating data and making necessary commands to process the data on the remote computer.
With so many online tools allowing scientists to store data related to research, there are efforts to coordinate the stored information and to improve collaboration online. Joint projects to free up stored data and make it available for influencing future research and present practice help.
This is where social media platforms become relevant as tools for sharing data. Scientists can describe their scientific methods and their results in real-time to a larger audience and interact with other scientists, just as they would in a laboratory environment (Ekins, Clark, & Williams, 2012). In their research Ekins, Clark and Williams (2012) looked at how the ODDT used Twitter to harvest information.
As a primary source of content, they relied on its APIs to poll and assimilate data. They were able to look at ODDT topics and content and then augmented their program to recognize emerging data sources and information streams that they deemed relevant to the research.
The project is ongoing, and the researchers explain that presently it can recognize molecular structures, reactions, and data sets presented in the social media network (Nagar et al., 2014). The research ushers a new way for scientists to observe and work around the growing menace of drug-sensitive and drug-resistant pathogens.
The problem for the scientific community has been the lack of data sharing publicly on a global scale. However, real international traction is achievable with the promise of the Twitter API and projects like ODDT (Marcus et al., 2011).
Conclusion
Actual usage of the Twitter API varies depending on desired results. A common feature is that applications will only function within the provisions provided by the API. It also depends on the ingenuity of system developers and application developers to come up with useful uses of their software.
Much of the research and scientific community, as well as ordinary users of curated information and reports generated by Twitter APIs need additional interpretation aids that third-party software mostly provides. It is important to note that the use of one mobile app like ODDT is yet to make an impact on the overall performance neglect of rare disease research.
Thus, it will take more research and, possibly, more applications that collect publicly shared content to come up with lasting changes that influence the medical research and drug discovery community.
References
Aboukhalil, R. (2013). Using the Twitter API to mine the Twitterverse. XRDS: Crossroads, The ACM Magazine for Students- Creativity + Computer Science, 19(4), 52-55.
Benhardus, J., & Kalita, J. (2013). Streaming trend detection in Twitter. International Journal of Web Based Communities, 9(1), 122-139.
Burton, S. H., Tanner, K. W., Giraud-Carrier, C. G., West, J. H., & Barnes, M. D. (2012). “Right time, right place” health communication on Twitter: Value and accuracy of location information. Journal of Medical Internet Research, 14(6), e156.
Ekins, S., Clark, A. M., & Williams, A. J. (2012). Open drug discovery teams: a chemistry mobile app for collaboration. Molecular Informatics, 31(8), 585-597.
Field, K., & O’ Brien, J. (2010). Cartoblography: Experiments in using and organising the spatial context of micro‐blogging. Transactions in GIS, 14(Suppl 1), 5-23.
Fitz-Gerald, S. (2010). Book review of: Twitter API: up and running by Kevin Makice. International Journal of Information Management, 30(3), 283-284.
Marcus, A., Bernstein, M. S., Badar, O., Karger, D. R., Madden, S., & Miller, R. C. (2011). Processing and visualizing data in tweets. SIGMOD Record, 40(4), 21-27.
Mills, S. (2011). FCJ-127 Concrete Software: Simondon’s mechanology and the techno-social. The Fibreculture Journal, 127(18). Web.
Morstatter, F., Pfeffer, J., Liu, H., & Carley, K. M. (2013). Is the sample good enough? Comparing data from Twitter’s streaming API with Twitter’s firehorse. Association for the Advancement of Artificial Intelligence. Web.
Nagar, R., Yuan, Q., Freifeld, C. C., Santillana, M., Nojima, A., Chunara, R., & Brownstein, J. S. (2014). A case study of the New York City 2012-2013 influenza season with daily geocoded twitter data from temporal and spatiotemporal perspectives. Journal of medical Internet Research, 16(10), e236.
Oussalah, M., Bhat, F., Challis, K., & Schnier, T. (2013). A software architecture for Twitter collection, search and geolocation services. Knowledge-Based Systems, 37, 105-120.
van de Velde, B., Meijer, A., & Homburg, V. (2014). Police message diffusion on Twitter: analysing the reach of social media communications. Behavior & Information Technology, 1-13.
The researchers carried out a comprehensive review of the existing information to determine some possible weaknesses and gaps in knowledge in order to come up with a strong conclusion. In this case, they realized that most of the past studies were largely cross-sectional and correlational in nature. This problem has made it difficult to make causal inferences. In addition, they noted that none of the previous studies had attempted to examine the impact of Twitter’s application in an educational setting or student management.
Research questions
The article was written within the guidelines of the conventional format for reporting research studies. The researchers have used both the review of literature and a strong purpose of the study to develop comprehensive, clear but encompassing study questions. Specifically, two research questions were addressed. First, they wanted to address the question “what is the effect of encouraging the use of Twitter for purposes relevant to education on student engagement?” Secondly, they wanted to answer the question “what is the effect of encouraging the use of Twitter for the purposes relevant to education on students’ grades per semester?” Therefore, it is evident that the researchers wanted to address two variables- “the impact of Twitter on engagement” and “the impact of Twitter on grades”.
Variables
A dependent variable is the measurable aspect used to show the effect of an action. On the other hand, an independent variable is the value that represents the input or cause of an action that produces a “measurable effect” on the aspect or phenomenon under study.
Therefore, in this case, the researchers’ independent variable was ‘the use of twitter’ among students in college. It was used to produce some effect on the phenomenon. On the other hand, the researchers’ dependent variables were two- “the impact on student engagement” and “the impact on student semester grades”. The two aspects were values that depend on another action (encouragement of Twitter use), but they cannot be directly manipulated by the researchers.
Study methods
The study design used indicates that a quantitative method was preferred. It involved statistical analysis of the questions prompted to students. Two groups of students were used- “a control group” and “a test group”. In addition, each student was assigned to one of the seven different sections of a ‘one-credit first-year course’ in health professional majors at a certain university in the US.
Participants
In total, the researchers used 132 students and assigned each student into one of the seven sections identified in the study. However, only 125 students out of the original number took the pre-test survey. The participation rate was 95%. A number of aspects were considered, including age (17 to 20 years), parenthood, prior exposure to social networking, ethnicity and gender. Specific questions were prompted in terms of survey questions. They were asked to discuss these questions using social networking via Twitter. Since the method wanted to examine the use of Twitter for education relevant purposes, a number of specific aspects were measured. These include book discussion, class reminders, academic and personal support, campus event reminders, class discussions and organized study groups. NSSE instrument was used to measure the outcomes.
Statistical tests
As mentioned above, the study was a quantitative research that heavily relied on statistical data to address the study questions. As such, statistical analysis was imperative to addressing the study questions. In this case, the researchers used NSSE instrument to measure the outcomes. In addition, it has psychometric properties it was a Likert-like scale in nature and was meant to measure the strength of the outcomes in figures and numbers. ANOVA was used to measure variance in engagement and grades.
Results
Using ANOVA results, the researchers found that both students and members of the faculty were highly engaged in the process of learning using Twitter. They found that the process of learning transcended class work in traditional settings. The study found that Twitter is an important tool in education because it increases the leaner’s’ ability to engage. In addition, it enhances the tutor’s ability to take active and participatory roles.
Value, strengths and limitations of the research
Noteworthy, the topic of study as well as the results are relatively rare in literature. As such, the value of the study is commendable because it yields information that is not only rare, but also fills the identified gap as well as providing evidence that Twitter can be used in improving class work rather than affecting student morals. In addition, the research’s strength is clear because the study used statistical analysis to measure the outcomes in an empirical setting.
Limitations
However, the study was prone to errors and biases because the student community at a single faculty and university is too small to represent the entire student population in the US. In addition, statistics are likely to cause errors and biases.
Application
I find the study applicable in providing additional information to the large topic of study “the positive impact of social media on students as opposed to the traditional thought that students’ morals, behavior and outcomes are degraded by social media”.
Reference
Junco, R., Heibergert, G., & Loken, E. (2010). The effect of Twitter on college student engagement and grades. Journal of computer assisted learning, 10(2), 1365-2729. Web.
Twitter is an example of a micro blog system; it is a social networking site used as a means of interaction and communication among people and also friends. It is a leading online community and is open to all like many social networking sites and a very powerful social marketing too that is used by many people for educational purposes. Twitter uses a Micro blogging system which is a Web 2.0 technology, a new form of blogging which lets the users publish online brief text updates, less than 140-200 characters, and images too. “The posts can be altered and viewed on the internet or conveyed as SMS, e-mail or through instant messaging clients. This system is used by all social networking sites like twitter and facebook and MySpace” (Lew, 2007).
Students and tutors have found twitter to be an effective way to solve the technical difficulties of class work since they are able to get instant answers and views about a particular problem hence assisting them in learning. Tutors also can use twitter to remind the students about home works or post the assignments to them the teachers just need to create a twitter feed on which the students can subscribe.Twiter can also be used by lectures to teach about technology, students can learn with it while at the same time interact with people.
Students use twitter for class discussions, which involve discussing questions and other issues that are learned in class by using a username account, it is also used to promote writing, editing skills and it improves literacy because twitter is all about writing and all information is conveyed through texts, it is also a source of knowledge because students can post question and get answers, students can a create groups that they can use to learn, and twitter also has a personal learning network to assist students at an individual level.
Conferences can be set up through Twitter and attendees can get to share their thoughts and those that are not able to attend can follow the discussions through twitter quick updates, students can also use twitter for research on their projects, educators can send assignments to students through twitter, announcements can also be made quickly to students and previous information can be retrieved. Twitter has also reference services and libraries’ from which one can easily access new books and information, this makes learning cheaper since information is accessed freely instead of using a lot of money in downloads or sending text messages to classmates to enquire about an issue.Teachers too can engage students in story telling sessions through twitter, and can also share among themselves good teaching methods through twitter.
Twitter has many advantages that makes a social network preferred by many.ome of these advantages are: it is easy to join, one does so by just creating an account with them, it takes less than a minute and also one can create as many accounts as you wish, twitter also has unique profile templates, which can be created through HTML mode or purchase it through legitimate dealers in different auction sites related to templates, the site limits people to short updates hence information on twitter is straight to the point hence there is no too much unnecessary information, there is one home page that enables people to get what they want very fast. One can get anyone they want on twitter and the same way they can get you hence enabling efficient and free networking and also one can access third parties.
Twitter updates people on new activities taking place, new information and new books that are available hence keeping you updated with new information available, twitter also allows use of any username as long as it is available hence keeping your information personal and anonymous, it is very useful and curriculum centered though not academically bound because its core business is socializing, through twitter one can is also able to connect to the real world interact, learn new cultures which enables one to cooperate and understand other people and also get to share their joys and sorrows.
Twitter has age, limits so as to protect minors because any thing can happen online including stalkers and bad sites, but in addition a private account is required for class work, twitter has track services through which one can track movies, words, names stores, instead of posting updates, people can protect their updates and restrict them only to friends that they approve hence making this is very appropriate for classroom work and discussions. Twitter is a possible substitute to emailing, instant messaging and online discussions, as means of coordinating with students and also it is fun to use. It is easy to create a twitter link to ones company or personal website with the availability of the flexible selection of free widgets and mini applications, and also twitter is easily accessible as long there is internet connectivity hence making it very reliable (Lew, 2007).
Twitter, like any other social networking site has its disadvantages, which include: Tweeter does not have many applications like its competitors do have sites for groups, videos blogs, marketplace and networking menus, one can only upload one picture in twitter which must be very small while in facebook one can upload even albums, in twitter people can not specify their audiences and hence chances of having stalkers following you are very high and this compromises ones privacy, it is also very simple, the profile is very lean and has little information about you hence making it not a very good social network which is their core business and this can be discouraging for those that are interested in socializing only but this is appropriate for educational purposes since the aim is to learn not to meet people.
Twitter updates keep appearing since they are not restricted and this can be very disturbing and inconvenient when in for lessons or when discussing an item with your group members especially when these updates are not educational, twitter can also be addictive and even distract students in a lecture or in discussions because some may prefer to chat with friends and this can lead to low grades and can also be treated as disrespect by the tutors which can lead to expulsion or other forms of punishment, when teachers are involved in twittering students can take this chance and intrude into the teacher’s private life which is rude and offensive, twitter can also be used to spread bad rumour about other people and can end up ruining their reputation and finally twitter can be very bad for students grammar because of the use of short forms to express themselves, which they can also do in class work and lead to bad performance (Java et al 2007).
In conclusion there is need for action to be taken to improve twitters services to its subscribers and some of the suggestions are: twitter can be bad for students due to the many spammers and even stalkers in it so there is a need for a private account for classroom work which can not be accessed by other people, students should be encouraged to post well thought updates and maintain anonymity so as to block followers who have nothing to do with class work. This does not mean that they should be discouraged from sending requests because twitter becomes useless without people to share or discuss with.
They should also be encouraged to practice self discipline to avoid getting addicted to twitter or consuming too much time on it, there should be a time limit for the amount of time one can tweet hence creating a restriction for too much tweeting. Before a class decides to use twitter they should make sure that every member is well informed on how to use twitter and understand it’s language so as to prevent mistakes being made and avoiding inconveniences, It also ensures that all students are able to access information on twitter, students should also be mixed when forming twitter groups so that the diverse need of all students are met. Students should also be taught how to protect their devices against viruses and data theft, how to customize twitter to meet their specific needs and interests.
People have criticized social networks and even propose that they should be banned because it is affecting children and teenagers as they spend most of their time on the internet, but with the current trend situation social networks are here to stay, because others claim it improves interpersonal communication skills. Parents who are the most complainers’ should embrace the networks and assist their children not to misuse this services and they should also understand that though the same sites their children can get employment and other good opportunities that can improve their lives.Twitter has proved to be an effective way to enhance learning the system though they should make various changes in their privacy settings and other issues mentioned above but the point that it has made learning easier can not overlooked.
Reference list
Java et al (2007). Why We Twitter. A journal of Understanding Microblogging Usage and ommunities, 2(10), p. 12-13.
Lew, A. A. (2007) Twitter. Tweets for Higher Education. Web.
“To Twitter or not to Twitter” article by Robert W. Lucky addresses the problem faced by the old generation in the usage of the internet. It aims main point of reference is that age is a determining factor in the usage of Twitter.
The author tries to elaborate his point of view through sharing his dilemma on whether to join Twitter. The article relates well with Lucky colleagues i.e. the old generation as it reveals issues they are struggling with. On the other hand, the youth understand the old generation perspective of the use of the social network.
Summary of the Article
The article begins with Lucky describing twitter and how it operates. This serves to inform all his audiences of Twitter in order to foster common understanding. Lucky refers to the young generation as “digital natives” (Lucky, 2010, p. 245), which implies that they are knowledgeable and experienced with technology. On the other hand, the older generations are termed as “digital immigrants” meaning they have adapted technology recently (Lucky, 2010, p. 245).
The author goes on to share his dilemma with technology in regard as to whether to use or not to use Twitter. Moreover, the author extends to share experiences with the youth and how they have changed his thoughts. It concludes by inquiring the importance of Twitter to the old people logically, but again leaves a room for personal judgments and opinions in regard Twitter usage. The article is generally interesting and intriguing.
Strengths of the Article
One of the articles strength is that the author is able to communicate effectively to broad spectra of audience i.e. both the old and the young are involved in the articles’ discussion. Despite the article dealing with the dilemma of the older generation in relation to technology it narrates incidences that they are conversant with.
Lucky is very cautious in usage of technical terms and goes to explain their meaning if he happens to use any. This is clearly seen when he defines Twitter and how it works in the introduction, descriptions of terms “digital native” and “digital immigrant” (Lucky, 2010, p. 245). This leads to greater understanding of this article by the audience. In addition, it makes the article informative to the older generation,and on the other hand entertaining to the younger generation.
Secondly, the article clearly illustrates how age is a determining factor in Twitter usage. It goes on to portray how both the old and young generations use Twitter differently. The youth use it for social networking while the old people search for professional usage of Twitter. Old people usage is supported by the author when points out that there is no need of posting that someone is awake as it is of no importance to the person reading the twit.
Contrary, a colleague of the author after twitting for a week felt connected to the network reflected when he said that he experienced “a sense of connectedness” which illustrates the author point, which is that Twitter serves a social purpose. Author portrays cultural element in technology when the old generation is part of online culture through the phrase inhabiting multiple identities, living a culture of sharing and by peer collaboration”(Lucky, 2010, p. 245).
Weakness of the Article
The authors fails to communicate effectively to global audience , as he struggles to maintain the balance of diversity involved and tends to be biased to the old generation opinions. This is evident when he has a personal disagreement with a young speaker in a conference hence indicating a communication barrier and alienation between the old and young generations.
The speaker, as an agent of the digital natives in article context, seems outrageous when he refers the digital immigrants, “pencil pushers” (Lucky, 2010, p. 246). In addition, when the author disguises the essence of twitting to indicate that someone is awake makes the young speaker who tweets every morning insignificant.
These illustrations go to reveal the potential of the author secluding the young generations. In contrast, Twitter works differently for the different generations the choice of examples for the article paints younger users as irrational and implicates them in “pointless, incessant barking” (Lucky, 2010, p. 246). This weakness is brought about by the authors desire to communicate to wide audience while he is relating to the old generation dilemma in Twitter usage.
Conclusion
The author in the “To Twitter or not to Twitter” article succeeds in portraying that there is a generational gap in the usage of Twitter.
The choice of illustrations though risks alienating the younger readers’ interest of a wide audience and despite being of old generational group keeps the voice of the article balanced. Consequently, this appeals and actively engages both the young and old in the articles discussion. The inquisitive nature and impartiality of the article makes its readers reflective of the way in which they use Twitter, rendering the article to be more of a reflective and an informative article.
Reference
Lucky, R. W. (2010). To Twitter Or Not to Twitter? In L. G. Kirszner, & S. R. Mandell, The Blair Reader: Exploring Issues and Ideas (pp. 244-246). Canada: Pearson Education.
Robert W. Lucky’s article titled “To Twitter or not to Twitter” discusses the dilemma that older internet users find themselves. Lucky (2010) seeks to share his dilemma on whether or not to join the social networking site. The main argument is that age is the key factor in determining the use of Twitter. Lucky (2010) targets a broad audience but has a bias for the older generation.
The article appeals to his contemporaries since the discussion relates to issues they are struggling with, while the younger generation will find some historical value in it and a feel of the perspective the older generation has on their use of Twitter. The author succeeds in sharing his dilemma with his audience.
The article starts by defining Twitter and describing how it works, based on the author’s perspective. This part informs the sections of the audience who may not have interacted with Twitter, thereby putting them on the same page as the rest. The author then delineates between the younger and the older generation. He refers to the younger generation as “digital natives” (Lucky, 2010, p. 245). This means that they grew up with technology as part of their daily experience.
On the other hand, he refers to the older generation as “digital immigrants” who have adapted to the technological changes in the recent years (Lucky, 2010, p. 245). The author then goes on to share personal experiences with younger persons in meetings. He provides a narrative on how they affected his thinking. The paper concludes by questioning the relevance of Twitter to the older generation in rational terms, but leaves room for the audience to arrive at their own conclusions regarding the use of Twitter.
The article had two distinct strengths. The first one is that the author succeeds in communicating to a broad audience. The distinction between the digital natives and digital immigrants invites both age groups to the discussion. While the article relates the struggles of the digital immigrants, it gives stories that digital natives are familiar.
The use of technical terms comes with special care. At the introduction, there is a full description of what Twitter is, and how it works. Inside the body, there are descriptions for the terms “digital native” and “digital immigrant” (Lucky, 2010, p. 245). This makes the article informative for the older generation, while it makes it entertaining for the younger generation who may find it amusing that there is need to describe how Twitter works.
The second key strength of the article is that it succeeds in demonstrating the role of age in the use of Twitter. In the latter sections, the discussion on whether to use Twitter in a forthcoming industry meeting provides an interesting look at the purpose Twitter serves for the two generations. The digital natives use it for social networking while the older one seems to try to find a way to use it for professional applications.
The author does not see the point in someone posting on Twitter that they are now awake. It does not seem to add any value to the audience viewing that Tweet. However, the story of the authors’ acquaintance who says that after using Twitter for a week he felt “a sense of connectedness” illustrates the author point, which is that Twitter serves a social purpose (Lucky, 2010, p. 246).
In addition, the author demonstrates that there is a cultural dimension to technology since the digital natives are part of an online culture and find expression in it by “inhabiting multiple identities, living a culture of sharing and by peer collaboration” (Lucky, 2010, p. 245).
The effort to sustain the interest of a wide audience creates one of the fundamental flaws of the article. After the introductory sections, the author struggles to maintain a voice fitting for the entire audience.
The details of the author’s personal disagreement with a young conference speaker alienate digital natives. The speaker, as a representative of the digital natives in the context of the article, comes off as preposterous when he calls the digital immigrants, “pencil pushers” (Lucky, 2010, p. 246). The author also makes the young speaker who tweets every morning appear petty.
These sections have the potential of alienating the younger sections of the author’s audience. While the author makes a good point of showing that, Twitter works differently for the different generations the choice of examples for the article paints younger users as irrational and implicates them in “pointless, incessant barking” (Lucky, 2010, p. 246).
This article is successful in bringing out the main point, which is that Twitter use varies on a generational level. The tone is not patronizing. This attracts both the young and the old readers to engage. Its reflective disposition and its undecided conclusion leave the readers thinking about how they use Twitter.
The author is successful in attracting the interest of a wide audience and in communicating the different ways that the generational divide influences the use of Twitter. The choice of illustrations though risks alienating the younger readers. In conclusion, the work is informative and stimulating.
Reference
Lucky, R. W. (2010). To Twitter Or Not to Twitter? In L. G. Kirszner, & S. R. Mandell, The Blair Reader: Exploring Issues and Ideas (pp. 244-246). Canada: Pearson Education.
The evolution of social networking sites (SNSs) has arguably strengthened social ties and created an environment of connectedness unseen with traditional forms of communication. Before the advent of social networking, people relied on the traditional forms of communication such as telephones to stay in touch with family and friends. Social networking sites including Twitter allow individuals to foster strong ties between friends as well as exchange news or views on public issues.
In this context, social networks provide a new cultural frontier allowing people to stay connected, both locally and globally. The social networks raise concerns over their impacts upon cultural and social institutions. However, the regular exchanges, besides allowing people to connect with the society, foster norms and trust, which are the key elements of any community life. Social networking sites are powerful tools for increasing public participation on social and cultural issues.
Cultural Effects of Social Networks
Social networking sites (SNSs), given their nature, facilitate the strengthening of social bonds and enhance access to cultural norms central to community life. For instance, twitter, through the ‘tweets’ feature allows individuals to monitor the activities of the friends, community, and family closely, thus maintaining an online connection similar to offline relationships.
In workplace settings, twitter and other SNS, allow sharing of vital information and comments about the organization. However, this raises security concerns with regard to information shared. Culturally, the management and employees sometimes share insights and thoughts about organizational and marketing issues through the social networks.
The SNSs represent a shift in the organization of communities by focusing primarily on individual interests. Unlike other online websites, SNSs according to Stern and Dillman (2006), “are structured with the individual at the center of their own community” (p. 417), which mirrors the offline culture of most communities.
However, of most concern is the privacy of the profile data. Twitter allows sharing of personal information with “followers” only. Still, the public nature of SNSs and the ability of a stranger to access such data raise serious security concerns. Additionally, an individual can assume different online and offline identities or include wrong information especially people with open profiles, which affect offline relationships and friendship.
Social impacts of SNSs
Unlike other communication media, SNSs have led to increased public participation particularly in the community and political issues affecting them. By creating trust, bridging online, and offline relationships, SNSs encourage participation of the public on various discussions, forums and civic participation including mass protests.
Of importance is the capacity of SNSs to create an online community with common interests or ideas and have much influence on social capital. In addition, the SNSs such as twitter allow sharing of information and pictures of social and political events. Thus, the SNSs serve to bond the social capital through friends and online communities.
Online interactions and regular exchange of information improve self-esteem and results to the high life satisfaction for individuals with low self-esteem (Stern, & Dillman, 2006, p. 409). However, SNSs sometimes affect negatively on social relationships when individuals adopt different online and offline identities. In twitter, an individual can choose to end a friendship through the “un friend” option. This normally arises when there is breach of trust and can affect even offline relationships.
Potential effects of SNSs on Face-to-Face Interactions
SNSs have allowed individuals to establish relationships with others outside their social group. Most online relationships are based on shared interests, as opposed to shared geography. This implies that the online friends are less likely to meet, which means that online interactions will eventually replace the face-to-face interactions. Stern and Dillman argue that, SNSs such as twitter usually allow individuals to maintain the existing offline relationships, as opposed to making new friends (2006, p. 411).
This means that individuals will most often interact online to share ideas or chat as opposed to interacting face-to-face. Additionally, online friends have common offline activities, which they can conveniently chat about as opposed to interacting face-to-face. (Stern, & Dillman, 2006, p. 417).
In this context, twitter and other SNSs enable users to interact with friends in circumstances where they are unable to socialize offline especially due to distance. Thus, users will more likely resort to online socialization with peers over face-to-face interactions in such situations.
Cultural Values and SNSs
Normally, online relationships are a reflection of offline interactions. In this regard, cultural values are not compromised by online interactions, as the offline friends constitute the majority of an individual’s online friends.
Since the SNSs essentially comprise of a community or “followers” in Twitter bound by common interests, the cultural values of social trust, social engagement and social ties are reinforced by SNSs. However, SNSs at the same time challenges privacy of information, leads to addiction, affects socialization and causes disintegration of many relationships.
Conclusion
Social networking sites such as twitter have significantly enhanced social ties compared to traditional communication forms. Due to their ease of usage, there is a high likelihood that they will replace face-to-face interactions. Looking into the future, SNSs are fast evolving along with the advancement in technology. Given their impact upon social engagement, SNSs will be a useful tool of expanding democracy and enhancing civic participation. However, privacy of personal data remains a serious concern.
Reference List
Stern, M., & Dillman, D. (2006). Community participation, social ties, and use of the internet. City & Community, 5(4), 409-424.