Multidimensional political spectrum identification and analysis

Leilei Zhu, Prasenjit Mitra

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

1 Scopus citations

Abstract

In this work, we show the importance of multidimensional opinion representation in the political context combining domain knowledge and results from principal component analysis. We discuss the differences of feature selection between political spectrum analysis and normal opinion mining tasks. We build regression models on each opinion dimension for scoring and placing new opinion entities, e.g. personal blogs or politicians, onto the political opinion spectrum. We apply our methods on the floor statement records of the United States Senate and evaluate it against the uni-dimensional representation of political opinion space. The experimental results show the effectiveness of the proposed model in explaining the voting records of the Senate.

Original languageEnglish (US)
Title of host publicationACM 18th International Conference on Information and Knowledge Management, CIKM 2009
Pages2045-2048
Number of pages4
DOIs
Publication statusPublished - Dec 1 2009
EventACM 18th International Conference on Information and Knowledge Management, CIKM 2009 - Hong Kong, China
Duration: Nov 2 2009Nov 6 2009

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

OtherACM 18th International Conference on Information and Knowledge Management, CIKM 2009
CountryChina
CityHong Kong
Period11/2/0911/6/09

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All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

Cite this

Zhu, L., & Mitra, P. (2009). Multidimensional political spectrum identification and analysis. In ACM 18th International Conference on Information and Knowledge Management, CIKM 2009 (pp. 2045-2048). (International Conference on Information and Knowledge Management, Proceedings). https://doi.org/10.1145/1645953.1646297