Political hashtag trends

Ingmar Weber, Venkata Rama Kiran Garimella, Asmelash Teka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

Political Hashtag Trends (PHT) is an analysis tool for political left-vs.-right polarization of Twitter hashtags. PHT computes a leaning for trending, political hashtags in a given week, giving insights into the polarizing U.S. American issues on Twitter. The leaning of a hashtag is derived in two steps. First, users retweeting a set of "seed users" with a known political leaning, such as Barack Obama or Mitt Romney, are identified and the corresponding leaning is assigned to retweeters. Second, a hashtag is assigned a fractional leaning corresponding to which retweeting users used it. Non-political hashtags are removed by requiring certain hashtag co-occurrence patterns. PHT also offers functionality to put the results into context. For example, it shows example tweets from different leanings, it shows historic information and it links to the New York Times archives to explore a topic in depth. In this paper, we describe the underlying methodology and the functionality of the demo.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages857-860
Number of pages4
Volume7814 LNCS
DOIs
Publication statusPublished - 2 Apr 2013
Event35th European Conference on Information Retrieval, ECIR 2013 - Moscow, Russian Federation
Duration: 24 Mar 201327 Mar 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7814 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other35th European Conference on Information Retrieval, ECIR 2013
CountryRussian Federation
CityMoscow
Period24/3/1327/3/13

Fingerprint

Seed
Polarization
Fractional
Methodology
Trends
Context
Archives

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Weber, I., Garimella, V. R. K., & Teka, A. (2013). Political hashtag trends. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7814 LNCS, pp. 857-860). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7814 LNCS). https://doi.org/10.1007/978-3-642-36973-5_102

Political hashtag trends. / Weber, Ingmar; Garimella, Venkata Rama Kiran; Teka, Asmelash.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7814 LNCS 2013. p. 857-860 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7814 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Weber, I, Garimella, VRK & Teka, A 2013, Political hashtag trends. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7814 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7814 LNCS, pp. 857-860, 35th European Conference on Information Retrieval, ECIR 2013, Moscow, Russian Federation, 24/3/13. https://doi.org/10.1007/978-3-642-36973-5_102
Weber I, Garimella VRK, Teka A. Political hashtag trends. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7814 LNCS. 2013. p. 857-860. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-36973-5_102
Weber, Ingmar ; Garimella, Venkata Rama Kiran ; Teka, Asmelash. / Political hashtag trends. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7814 LNCS 2013. pp. 857-860 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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