Identifying Policy Agenda Sub-Topics in Political Tweets based on Community Detection

dc.contributor.author Tavanapong, Wallapak
dc.contributor.author Iyer, Rohit
dc.contributor.author Wong, Johnny
dc.contributor.author Tavanapong, Wallapak
dc.contributor.author Peterson, David
dc.contributor.author Peterson, David
dc.contributor.department Computer Science
dc.contributor.department Political Science
dc.date 2018-02-19T00:00:17.000
dc.date.accessioned 2020-06-30T01:54:39Z
dc.date.available 2020-06-30T01:54:39Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2017
dc.date.embargo 2017-10-18
dc.date.issued 2017-01-01
dc.description.abstract <p>The explosive use of twitter in the political landscape presents new avenues for tracking political conversations at federal and state level. Tweets are used by state and federal government bodies to present citizens with information about future and present policies. It is also used by political candidates to express their views on policy changes, laws and to campaign for legislative body elections, the most recent example being the 2016 US presidential elections. In this paper, we use supervised learning, textual semantic similarity and community detection techniques to find actively discussed policy agenda sub-topics among political tweets within a certain time period.</p>
dc.description.comments <p>This article is published as Iyer, Rohit, Johnny Wong, Wallapak Tavanapong, and David AM Peterson. "Identifying Policy Agenda Sub-Topics in Political Tweets based on Community Detection." Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/cs_conf/43/
dc.identifier.articleid 1041
dc.identifier.contextkey 10917644
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath cs_conf/43
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/19851
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/cs_conf/43/2017_IdentifyingPolicy.pdf|||Sat Jan 15 00:15:12 UTC 2022
dc.subject.disciplines Computer Sciences
dc.subject.disciplines Databases and Information Systems
dc.subject.disciplines Models and Methods
dc.subject.disciplines Political Science
dc.subject.disciplines Programming Languages and Compilers
dc.subject.disciplines Software Engineering
dc.subject.keywords twitter
dc.subject.keywords policy agenda
dc.subject.keywords sub-topics
dc.subject.keywords community detection
dc.subject.keywords convolutional neural networks
dc.subject.keywords semantic similarity
dc.title Identifying Policy Agenda Sub-Topics in Political Tweets based on Community Detection
dc.type article
dc.type.genre article
dspace.entity.type Publication
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