Abstract

Blogosphere plays an increasingly important role as a forum for public debate. In this paper, given a mixed set of blogs debating a set of political issues from opposing camps, we use signed bipartite graphs for modeling debates, and we propose an algorithm for partitioning both the blogs, and the issues (i.e. topics, leaders, etc.) comprising the debate into binary opposing camps. Simultaneously, our algorithm scales both the blogs and the underlying issues on a univariate scale. Using this scale, a researcher can identify moderate and extreme blogs within each camp, and polarizing vs. unifying issues. Through performance evaluations we show that our proposed algorithm provides an effective solution to the problem, and performs much better than existing baseline algorithms adapted to solve this new problem. In our experiments, we used both real data from political blogosphere and US Congress records, as well as synthetic data which were obtained by varying polarization and degree distribution of the vertices of the graph to show the robustness of our algorithm.

Original languageEnglish (US)
Title of host publicationProceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013
Pages168-173
Number of pages6
DOIs
StatePublished - 2013
Event2013 ASE/IEEE Int. Conf. on Social Computing, SocialCom 2013, the 2013 ASE/IEEE Int. Conf. on Big Data, BigData 2013, the 2013 Int. Conf. on Economic Computing, EconCom 2013, the 2013 PASSAT 2013, and the 2013 ASE/IEEE Int. Conf. on BioMedCom 2013 - Washington, DC, United States
Duration: Sep 8 2013Sep 14 2013

Other

Other2013 ASE/IEEE Int. Conf. on Social Computing, SocialCom 2013, the 2013 ASE/IEEE Int. Conf. on Big Data, BigData 2013, the 2013 Int. Conf. on Economic Computing, EconCom 2013, the 2013 PASSAT 2013, and the 2013 ASE/IEEE Int. Conf. on BioMedCom 2013
CountryUnited States
CityWashington, DC
Period9/8/139/14/13

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Blogs
Polarization
Experiments

ASJC Scopus subject areas

  • Software

Cite this

Gokalp, S., Temkit, M., Davulcu, H., & Toroslu, I. H. (2013). Partitioning and scaling signed bipartite graphs for polarized political blogosphere. In Proceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013 (pp. 168-173). [6693329] https://doi.org/10.1109/SocialCom.2013.32

Partitioning and scaling signed bipartite graphs for polarized political blogosphere. / Gokalp, Sedat; Temkit, M'hamed; Davulcu, Hasan; Toroslu, I. Hakki.

Proceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013. 2013. p. 168-173 6693329.

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

Gokalp, S, Temkit, M, Davulcu, H & Toroslu, IH 2013, Partitioning and scaling signed bipartite graphs for polarized political blogosphere. in Proceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013., 6693329, pp. 168-173, 2013 ASE/IEEE Int. Conf. on Social Computing, SocialCom 2013, the 2013 ASE/IEEE Int. Conf. on Big Data, BigData 2013, the 2013 Int. Conf. on Economic Computing, EconCom 2013, the 2013 PASSAT 2013, and the 2013 ASE/IEEE Int. Conf. on BioMedCom 2013, Washington, DC, United States, 9/8/13. https://doi.org/10.1109/SocialCom.2013.32
Gokalp S, Temkit M, Davulcu H, Toroslu IH. Partitioning and scaling signed bipartite graphs for polarized political blogosphere. In Proceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013. 2013. p. 168-173. 6693329 https://doi.org/10.1109/SocialCom.2013.32
Gokalp, Sedat ; Temkit, M'hamed ; Davulcu, Hasan ; Toroslu, I. Hakki. / Partitioning and scaling signed bipartite graphs for polarized political blogosphere. Proceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013. 2013. pp. 168-173
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