The use of social media impacts individual and group participation in political activism. Social networking sites offer some affordances that can be employed by political activists to communicate with each other, mobilize movements, and disseminate information to increase public awareness about social issues. Consequently, the affordances of social media have played a major role in increasing citizen participation in political discourses all around the world (Gleason, 2013; Halpern & Gibbs, 2012; Hayes, Carr & Wohn, 2016; Lawrence, Molyneux, Coddington, & Holton, 2014). However, online political activism can be influenced by software robots which can interact with individuals on social media to emulate their behavior and influence their political opinion. For example, Bessi & Ferrara (2016) collected and analyzed 20 million tweets generated by approximately 2.8 million different users between 16 September and 21 October 2016 associated with the 2016 U.S. presidential election; they estimated that about 400,000 bots — “nearly 15 percent of the total population under study” — were engaged in the political discussion about the presidential election. Therefore, it can be said that the existence of social bots can affect the social media landscape, influence democratic political discussion and ultimately alter public opinion; with this in mind, further study is required to expand our knowledge and understanding of social bots’ effects.
This study makes use of the theory of affordances to explore how the affordances of social media have been effectively used by individuals in their political activism, how social robots affect the social media landscape and users’ public opinions, and how various social media affordances shape debate networks and influence discussion. To do so, this study will use the case study of ‘building the wall’ to analyze social bots’ functionality and their interaction on social media to demonstrate how they can affect human political communication. This study has collected the tweets from January 2019, when the topic of building or not building the wall between the United States and Mexico was at the center of public attention, that contain the hashtag #BuildTheWall. The tweets were collected via Sysomos, a social research platform that provides search and data collection for billions of online conversations, including Twitter. This study also uses Botometer, which is an open access software, to identify spam accounts and explores their interaction on Twitter to examine how many spam accounts participated in ‘building the wall’ discourse.
Increasing public awareness about bots’ activities can be beneficial for social media’s active users since this knowledge can assist them in understanding how to react to content published on these platforms; it is also valuable for those who are not using these platforms simply because if bots stay unrecognizable, blending themselves in with human users, gaining more power to affect public opinion and eventually influencing public decision-making, the results will also impact those who are not using these platforms.