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University of Maryland

EXPLORATORY GRAPH BASED BOT DETECTION APPLICATION ON REDDIT SUBNETWORKS

Abstract

dc:description.abstract

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.

Degree

thesis:*
Department dc:contributor.department
Library & Information Services
Year dc:date.issued
2021

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Cruz, Gabriel
Advisor dc:contributor.advisor
  • Golbeck, Jennifer

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:drum.lib.umd.edu:1903/27458

Chain of custody

source
Harvested from
University of Maryland
Base URL
api.drum.lib.umd.edu/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Cruz, Gabriel. EXPLORATORY GRAPH BASED BOT DETECTION APPLICATION ON REDDIT SUBNETWORKS. 2021. http://hdl.handle.net/1903/27458