Evaluating collective action theory-based model to simulate mobs
Bibliographic Data
| ID | 4656464 |
|---|---|
| Authors | Samer Al-Khateeb (0000-0001-6327-5720, Creighton University, corresponding author), Jack Burright (Creighton University), Neil Agarwal (0000-0002-5612-4753, University of Arkansas at Little Rock), Nitin Agarwal (0000-0003-0256-3897) |
| Year | 2024 |
| Volume | 14 |
| Issue | 1 |
| Publication date | 2024-07-02 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-024-01284-z |
| OpenAlex | W4400247907 |
| Language | EN |
| Citations received | 1 |
| References cited | 23 |
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
Anonymity · Collective action · Computer security · Data science · Happening · Internet privacy · Political science · Politics · Social media · World Wide Web · Complex Network Analysis Techniques · Computer Science · Digital Marketing and Social Media · Opinion Dynamics and Social Influence · Artificial Intelligence
| Citations per year | 1 |
|---|---|
| Citation span | 2025 - 2025 (1) |
| Highly cited | No |