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Abstract A mob is an event that is organized via social media, email, SMS, or other forms of digital communication technologies in which a group of people (who might have an agenda) get together online or offline to collectively conduct an act and then disperse (quickly or over a long period). In recent years, these events are increasingly happening worldwide due to the anonymity of the internet, affordability of social media, boredom, etc. Studying such a phenomenon is difficult due to a lack of data, theoretical underpinning, and resources. In this research, we use the Agent-Based Modeling (ABM) technique to model the mobbers and the Monte Carlo method to assign random values to the factors extracted from the theory of Collective Action and conduct many simulations. We also leverage our previous research on Deviant Cyber Flash Mobs to implement various scenarios the mobber could face when they decide to act in a mob or not. This resulted in a model that can simulate mobs, estimate the mob success rate, and the needed powerful actors (e.g., mob organizers) for a mob to succeed. We finally evaluate our model using real-world mob data collected from the Meetup social media platform. This research is one step toward fully understanding mob formation and the motivations of its participants and organizers.
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Political Communication, Computational Propaganda, and Autonomous Agents: Introduction
The Internet certainly disrupted our understanding of what communication can be, who does it, how, and to what effect. What constitutes the Internet has always been an evolving suite of technologies and a dynamic set of social norms, rules, and patterns of use. But the shape and character of digital communications are shifting again—the browser is no longer the primary means by which most people encounter information infrastructure. The bulk of digital communications are no longer between people but between devices, about people, over the Internet of things. Political actors make use of technological proxies in the form of proprietary algorithms and semiautomated social actors—political bots—in subtle attempts to manipulate public opinion. These tools are scaffolding for human control, but the way they work to afford such control over interaction and organization can be unpredictable, even to those who build them. So to understand contemporary political communication—and modern communication broadly—we must now investigate the politics of algorithms and automation.
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- Award ID(s):
- 1450193
- PAR ID:
- 10021331
- Date Published:
- Journal Name:
- International journal of communication
- Volume:
- 10
- ISSN:
- 0975-640X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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