Full metadata
Title
Categorizing and Discovering Social Bots
Description
Bots tamper with social media networks by artificially inflating the popularity of certain topics. In this paper, we define what a bot is, we detail different motivations for bots, we describe previous work in bot detection and observation, and then we perform bot detection of our own. For our bot detection, we are interested in bots on Twitter that tweet Arabic extremist-like phrases. A testing dataset is collected using the honeypot method, and five different heuristics are measured for their effectiveness in detecting bots. The model underperformed, but we have laid the ground-work for a vastly untapped focus on bot detection: extremist ideal diffusion through bots.
Date Created
2015-05
Contributors
- Karlsrud, Mark C. (Author)
- Liu, Huan (Thesis director)
- Morstatter, Fred (Committee member)
- Barrett, The Honors College (Contributor)
- Computing and Informatics Program (Contributor)
- Computer Science and Engineering Program (Contributor)
- School of Mathematical and Statistical Sciences (Contributor)
Topical Subject
Resource Type
Extent
12 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Series
Academic Year 2014-2015
Handle
https://hdl.handle.net/2286/R.I.28741
Level of coding
minimal
Cataloging Standards
System Created
- 2017-10-30 02:50:57
System Modified
- 2021-08-11 04:09:57
- 3 years 1 month ago
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