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With the advent of algorithms and the strengthening of artificial intelligence (AI) technological capabilities, the ways in which communication has been delivered in society have changed. This is especially evident in the step away from mass communication to the increasingly more targeted, automated, and personalized communication. Algorithms have been increasingly used for automated decision-making, with the data-driven technologies used for making decisions without humans’ interference. In social media, algorithms have become quite essential as they represent the way of sorting posts in the online feed of users based on their relevance to them instead of the time of publishing. This means that social media can control which information is to be seen by users in their feeds first as related to the higher likelihood that they want to see it.
It is essential to study algorithmic media because their understanding can allow businesses and individuals to promote themselves or products that they offer online. Understanding which information is more likely to get pushed in algorithmic media is possible using both qualitative and quantitative methodologies. Besides, there are some challenges that come with the study of algorithms in media, especially when it comes to users’ privacy. Researchers have described that algorithmic media has negative effects, such as undesirable or disturbing selection, information manipulation, outputs to disrupt public discourse, and others. Research on algorithmic media can be extensive because algorithms are constantly changing and evolving due to societal events, with people having to adapt to them in order to use and understand them better. As long as online content will be expanding and changing, algorithmic media will also have to be transformed to go hand-in-hand with the latest trends in the online environment.
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