A Network Topology Approach to Bot Classification
Social and Information Networks
2018-09-18 v1 Physics and Society
Abstract
Automated social agents, or bots, are increasingly becoming a problem on social media platforms. There is a growing body of literature and multiple tools to aid in the detection of such agents on online social networking platforms. We propose that the social network topology of a user would be sufficient to determine whether the user is a automated agent or a human. To test this, we use a publicly available dataset containing users on Twitter labelled as either automated social agent or human. Using an unsupervised machine learning approach, we obtain a detection accuracy rate of 70%.
Cite
@article{arxiv.1809.06190,
title = {A Network Topology Approach to Bot Classification},
author = {Laurenz A Cornelissen and Richard J Barnett and Petrus Schoonwinkel and Brent D. Eichstadt and Hluma B. Magodla},
journal= {arXiv preprint arXiv:1809.06190},
year = {2018}
}