Financial Information in Social Media Networks

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Technological advancement is one of the major characteristics of the contemporary world. Technology has penetrated every sphere of modern life and every field and industry of business and science. Financial analysis and forecasting have benefited significantly from the integration of technology. At the same time, this kind of integration has resulted in a variety of changes and adjustments that significantly transformed the specialty. In particular, the collection of information is the core activity underlying analysis and forecasting practices and enabling informed projecting in any financial specialization. In the contemporary world, in addition to the traditional sources of financial information such as the business publications, scholarly research, and financial reports of business organizations, there exist digital resources storing detailed and valuable financial information, thus making it accessible to different stakeholders and other types of readers.

Some of the examples of digital sources of financial information are the news portals on the Internet that post relevant financial reports as soon as the news appears. Such resources prove to be of extreme value to investors and other financial decision-makers because the most recent changes in the marker are what interests them on a daily basis. This is the case because the newest financial changes immediately contribute to the overall situations in the industries and businesses and drive the decision-making process of business leaders. In that way, they carry more professional value than reviews and reports that only reflect the tendencies of the past. In addition to the news portals focused specifically on finding and publishing finance-related information, there exist social media resources where the choices of consumers and market fluctuations can be analyzed in correlation with social trends and used for financial forecasting based on concepts and theories from behavioral economics. In particular, Chung and Liu (2011) stated that one of the core principles of behavioral economics explains that people’s consumption patterns and choices are very often irrational and driven either by emotions or the judgments of others.

In that way, the analysis of customer behaviors and other financial information on the online social platforms can be a powerful forecasting tool helping to see and understand the consumers’ intention to purchase, tastes, preferences, and ideas concerning different goods and industries, as well as the factors that contribute to the formation of certain tendencies in consumer decision-making. Since information is handled and presented differently on various social networks and news portals, there are many strategies helping to collect and process the most relevant data. In this paper, the focus is on the exploration of means and techniques of collecting and processing financial information from Internet resources. In particular, the financial data that can be found on the world-renowned social network Twitter and how it can be approached by a financial forecaster for the creation of a reliable basis for the financial decision-making is discussed.

The unique benefits of Twitter as the Web resource for the statistical data mining are based on the concise and highly informative nature of its postings (also known as tweets), since there is a limit to their length (140 characters), which makes the Twitter newsfeed comprehensible and easy to follow and read (Chung & Liu 2011). The short messages on Twitter filled with condensed information seem particularly useful and effective as the sources of the most recent and dynamic financial information suitable for research.

Reference

Chung C & Liu, L 2011, Predicting stock market fluctuations from twitter: an analysis of the predictive powers of real-time social media. Web.

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