#BotOrNot #BotOrNot #BotOrNot

In recent years, Twitter has faced a growing issue of spam infiltrating its network. The hijacking of social media accounts has become a significant threat, with motives ranging from identity theft to manipulating public perception. Building on our previous research, Engineering Your Social Network to Detect Fraudulent Profiles, this paper investigates the presence of spam bots on Twitter. We introduce an algorithm designed to differentiate between spam bots and genuine user accounts by leveraging a JavaScript testing framework that interacts with Twitter’s REST API. After analyzing a dataset of 700 Twitter accounts, our algorithm identified that approximately 11% were bots.