Identifying Policy Agenda Sub-Topics in Political Tweets based on Community Detection
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 | ||
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 | |
relation.isAuthorOfPublication | f9b67a19-5d18-4682-9a80-4f91f92018a2 | |
relation.isAuthorOfPublication | 0bd00a69-d478-41ef-a7de-7bf84603c413 | |
relation.isOrgUnitOfPublication | f7be4eb9-d1d0-4081-859b-b15cee251456 | |
relation.isOrgUnitOfPublication | a4a018a7-4afa-4663-ba11-f2828cbd0a15 |
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