MS, University of Cincinnati, 2020, Education, Criminal Justice, and Human Services: Information Technology-Distance Learning

In 2017, Twitter acknowledged the presence of bots – automated or fake accounts, controlled by either foreign governments or U.S. citizens posing as fake online personas. These accounts targeted and interacted with users using certain politically inclined keywords and posting massive amounts of false and misleading information. Consequently, bots posing as Americans were loud voices that led to a divisive social and political climate. Simultaneously, distrust in mainstream news sources was plummeting causing more people to use social media as their main source of information. While tools exist that can determine if a given Twitter account is an authentic user or bot, they are not the most accessible products. Many require searching for an individual screen name on a separate web page, or advanced programming skills to analyze lists of users. This study examined this gap and determined the system and information requirements to develop a browser plugin that can detect bots, and the political leaning of a user's social media feed. By examining both open-source projects and public API's, this work was able to narrow down the requirements while providing the guidelines to build such a plugin.

Committee: Shane Halse Ph.D. (Committee Chair); Jess Kropczynski Ph.D. (Committee Member) Subjects: Information Technology