@inproceedings{757e3943f5944e4bb8653cb633b6ce5e,
title = "Assessing temporal and spatial features in detecting disruptive users on Reddit",
abstract = "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.",
author = "Ashford, {James R.} and Turner, {Liam D.} and Whitaker, {Roger M.} and Alun Preece and Diane Felmlee",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 12th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020 ; Conference date: 07-12-2020 Through 10-12-2020",
year = "2020",
month = dec,
day = "7",
doi = "10.1109/ASONAM49781.2020.9381426",
language = "English (US)",
series = "Proceedings of the 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "892--896",
editor = "Martin Atzmuller and Michele Coscia and Rokia Missaoui",
booktitle = "Proceedings of the 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020",
address = "United States",
}