2026-09-19T16:51:24Zhttps://api.drum.lib.umd.edu/server/oai/request

oai:drum.lib.umd.edu:1903/274582022-03-12T11:53:37Zcom_1903_2249com_1903_1631com_1903_2col_1903_2780col_1903_3

Golbeck, Jennifer Cruz, Gabriel Digital Repository at the University of Maryland University of Maryland (College Park, Md.) Library & Information Services 2021-07-14T05:35:19Z 2021-07-14T05:35:19Z 2021 https://doi.org/10.13016/f7on-gbry http://hdl.handle.net/1903/27458 Methods for detecting bots have traditionally focused on implementing machine learning systems to classify abnormal behavior. We focus on abnormal term usage as a markerof bot behavior around politically charged language regarding the Covid-19 pandemic on Reddit. We look at multiplex networks abstracted from different subreddits around six terms. We then use novel measures to quantify the differences between the layers in all of these multiplex networks to detect abnormalities in term usage over time and to quantify the differences between subreddit aggregated networks. We conclude that there is not enough evidence to declare that any one term investigated demonstrated an abnormal rate of usage over time. Additionally, none of the aggregated networks demonstrated differences between them indicating that the usage of the terms themselves is not different. We hope to demonstrate the efficacy of this graph-based technique to potentially detect botnet structures on social media. en EXPLORATORY GRAPH BASED BOT DETECTION APPLICATION ON REDDIT SUBNETWORKS Thesis Information science multiplex network network reddit open.access