Twitter Bot Detection using Social Network Analysis
Publication Date
1-1-2022
Document Type
Conference Proceeding
Publication Title
Proceedings - 2022 4th International Conference on Transdisciplinary AI, TransAI 2022
DOI
10.1109/TransAI54797.2022.00022
First Page
87
Last Page
88
Abstract
Twitter is an online platform that provides social networking services for hundreds of millions of active accounts. However, an estimation of 48 million accounts on Twitter are not human. These accounts are bots, which are automated software that control accounts. Identifying Twitter bots is desirable as human can view Twitter bots as a credible source of information. Existing methods to detect Twitter bots are mainly feature-based and text-based. In this paper, we propose a graph-based approach to detect Twitter bots as an alternative to the traditional bot detection methods. The paper outlines the data collection process, behaviors to observe in an account, and a proposal for a machine learning classifier utilizing these behaviors.
Keywords
graph classification, machine learning, social network analysis, Twitter bots
Department
Computer Science
Recommended Citation
Thi Bui and Katerina Potika. "Twitter Bot Detection using Social Network Analysis" Proceedings - 2022 4th International Conference on Transdisciplinary AI, TransAI 2022 (2022): 87-88. https://doi.org/10.1109/TransAI54797.2022.00022
