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Survey of political bots on Twitter
Descriptive
TitleInfo
Title
Survey of political bots on Twitter
Name
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(type = family)
Troupe
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(type = given)
David
NamePart
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1988-
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David Troupe
Role
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author
Name
(type = personal)
NamePart
(type = family)
Birget
NamePart
(type = given)
Jean-Camille
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Jean-Camille Birget
Affiliation
Advisory Committee
Role
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(authority = RULIB)
chair
Name
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NamePart
Rutgers University
Role
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(authority = RULIB)
degree grantor
Name
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NamePart
Camden Graduate School
Role
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school
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Text
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theses
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2019
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2019-01
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2019
Place
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xx
Language
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(type = code)
eng
Abstract
(type = abstract)
Bots are software applications that execute automated tasks called scripts over the Internet. Bots have become predominant on social media platforms like Twitter, and automate their interactions with other users. Political Twitter bots have emerged that focus their activity on elections, policy issues, and political crises. These political bots have faced increased scrutiny as a result of their association with online manipulation via the spread of misinformation. As bots have become more sophisticated, research has focused on advanced methods to detect their presence on social media platforms. However, little research has been performed on the overall presence of political bots and their dynamic response to political events. The research that has been performed on political bots focuses on these bots in the context of scheduled political events, such as elections. In this paper, we explore the bot response to an unexpected political event, describe the overall presence of political bots on Twitter, and design and employ a model to identify them based on their user profile alone. We collected data for more than 700,000 accounts tweeting with hashtags related to political events in the United States between May 2018 and October 2018. We designed a machine learning algorithm using user profile features alone that achieves approximately 97.4% accuracy in identifying political Twitter bots. In our analysis, we found (1) new bot accounts are created in response to political events, (2) bot accounts are more active during political controversies, (3) the number of tweets an account has favorited (liked) is a strong determinant of bot status.
Subject
(authority = RUETD)
Topic
Computer Science
Subject
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Topic
Twitterbots
Subject
(authority = ETD-LCSH)
Topic
Political participation
RelatedItem
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TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
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ETD
Identifier
ETD_9461
PhysicalDescription
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electronic resource
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application/pdf
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text/xml
Extent
1 online resource (63 pages : illustrations)
Note
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M.S.
Note
(type = bibliography)
Includes bibliographical references
Note
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by David Troupe
RelatedItem
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TitleInfo
Title
Camden Graduate School Electronic Theses and Dissertations
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rucore10005600001
Location
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(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/t3-8xsa-0033
Genre
(authority = ExL-Esploro)
ETD graduate
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Rights
RightsDeclaration
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The author owns the copyright to this work.
RightsHolder
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Name
FamilyName
Troupe
GivenName
David
Role
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RightsEvent
Type
Permission or license
DateTime
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2018-12-24 14:21:44
AssociatedEntity
Name
David Troupe
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Copyright holder
Affiliation
Rutgers University. Camden Graduate School
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
RULTechMD
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ETD
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windows xp
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1.4
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2019-01-04T11:57:58
DateCreated
(point = end);
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2019-01-04T11:57:58
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