Are social bots a real threat? An agent-based model of the spiral of silence to analyse the impact of manipulative actors in social networks. Issue 4 (4th July 2019)

• Record Type: Journal Article
• Authors: Ross, Björn; Pilz, Laura; Cabrera, Benjamin; Brachten, Florian; Neubaum, German; Stieglitz, Stefan
• Is Part Of: European journal of information systems. Volume 28:Issue 4(2019)
• Page Start: 394
• Page End: 412
• Publication Date: 2019-07-04
• Subjects: Prof. Frantz Rowe; Dr. Iris Junglas; Spiral of silence -- agent-based modelling -- social bots -- simulation -- network analysis; Information technology -- Periodicals; Information technology -- Europe -- Periodicals; Management information systems -- Periodicals; Management information systems -- Europe -- Periodicals; 658.403805
• DOI: 10.1080/0960085X.2018.1560920
• Languages: English
• ISSNs: 0960-085X

Abstract

ABSTRACT: Information systems such as social media strongly influence public opinion formation. Additionally, communication on the internet is shaped by individuals and organisations with various aims. This environment has given rise to phenomena such as manipulated content, fake news, and social bots. To examine the influence of manipulated opinions, we draw on the spiral of silence theory and complex adaptive systems. We translate empirical evidence of individual behaviour into an agent-based model and show that the model results in the emergence of a consensus on the collective level. In contrast to most previous approaches, this model explicitly represents interactions as a network. The most central actor in the network determines the final consensus 60–70% of the time. We then use the model to examine the influence of manipulative actors such as social bots on public opinion formation. The results indicate that, in a highly polarised setting, depending on their network position and the overall network density, bot participation by as little as 2–4% of a communication network can be sufficient to tip over the opinion climate in two out of three cases. These findings demonstrate a mechanism by which bots could shape the norms adopted by social media users.