A Comparative Analysis of Facebook and Twitter Bots

The increasing level of sophistication in the field of machine learning and artificial intelligence has engendered the creation of automated programs called \u27bots\u27. Bots are created for varied reasons, and it has become imperative to evaluate the impact of bots on the social media ecosystem and consequently on our daily lives. However, despite the ubiquity of bots, very little research has been conducted to compare their trends and impacts on the social media ecosystem. To address this gap in bot research, we perform a comparative analysis of Facebook and Twitter bots, in terms of their popularity and impact on the society. This paper sets the foundation to allow for subsequent, more detailed studies into this subject area. Analyzing trends of these emerging technologies can provide insight into identifying their importance and roles in our everyday life. We provide a brief background of the subject, such as types of social bots and their utility, bot detection techniques, and the impact they have had on society. We then utilize the IBM Watson cognitive search and content analytics engine to examine the public perception of these bots. We also use the Google query volumes to investigate the trends of search terms related to Facebook and Twitter bots. Our findings suggest that there is a slightly higher public acceptance of Facebook bots as compared to Twitter bots. Furthermore, the utilization of bots on Online Social Networks (OSNs) is on the rise. Originally, bots were developed as a tool for driving user engagements on social media platforms. However, today bots are increasingly being used to convey mis/disinformation and political propaganda