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Assessing temporal and spatial features in detecting disruptive users on Reddit

Ashford, James, Turner, Liam ORCID:, Whitaker, Roger ORCID:, Preece, Alun ORCID: and Felmlee, Diane 2020. Assessing temporal and spatial features in detecting disruptive users on Reddit. Presented at: 10th Workshop on Social Network Analysis in Applications (SNAA 2020), The Hague, Netherlands, 3 August 2020.

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Trolling, echo chambers and general suspicious behaviour online are a serious cause of concern due to their potential disruptive effects beyond social media. This motivates a better understanding of the characteristics of disruptive behaviour on the internet and methods of detection. In this work we focus on Reddit which provides a rich social media platform for community focused interactions. Using network representations of user activity alongside temporal statistics and other features we assess the behaviour of a sample of potentially disruptive users, based on their assigned comment karma (an aggregate of a user's comment up-votes), relative to the wider population. We explore how these signals contribute to the accurate prediction of disruptive users, and note that this is achieved without requiring any semantic analysis. Our results show that it is possible to detect signs of disruptive behaviour with good accuracy using limited inputs that are primarily based on the reply patterns that users generate. This is of potential value for large-scale detection problems and operation across different languages.

Item Type: Conference or Workshop Item (Paper)
Status: In Press
Schools: Computer Science & Informatics
Crime and Security Research Institute (CSURI)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
U Military Science > U Military Science (General)
Funders: DAIS-ITA
Date of First Compliant Deposit: 10 December 2020
Date of Acceptance: 7 December 2020
Last Modified: 27 Nov 2022 12:52

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