Bot Politics: The Affordances of Twitter and Nonhuman Participation

Social networking sites have had an indisputable impact on the realm of political communications, increasing political discourses all around the world. Social media platforms offer some affordances that can be employed by users to facilitate their political activism. However, online political activism can be influenced by software robots which can interact on social media to emulate human users’ behaviour and influence their political opinion. This dissertation employs the theory of affordances and explores how the affordances of Twitter, including shareability, direct communication, dynamic interaction, searchability, and identifiability function in practice and have been used to facilitate the political engagement of human and nonhuman users. To do so, this dissertation uses the case study of the 2017 Women’s March in the United States to articulate the affordances of Twitter and explores how human users employ the affordances of this platform in their political engagement. The result of this analysis indicates that the affordances of Twitter such as shareability (tweeting, retweeting, hashtags), and dynamic interaction (liking) were the most prevalent affordances of this platform during the Women’s March. In addition, the case study of “building the wall” is used to analyze social bots’ function, behaviour, and interaction on Twitter, to demonstrate to what extend bots are capable of using the affordances of Twitter. This study demonstrates that bots use the affordance of shareability (retweeting) and dynamic interaction (liking) more than other affordances. However, this study did not find convincing evidence that these bots are able to generate new content, cultivate meaningful discussions, or directly provide responses to other tweets. The theory of affordances accredits two main components, the human and the environment, and claims that affordances are properties that the environment offers to any human who perceives and uses them. However, focusing on two main elements creates substantial limitations for employing the theory to explore artificial intelligence and self-improving machines. This study demonstrates that bots are capable of using some of the affordances of Twitter and imitate human-like performance to some degree. Therefore, by including a third component — nonhuman smart actors— this study proposes a new definition for the theory of affordances, which is a core contribution of this dissertation.