Browse > Article
http://dx.doi.org/10.7472/jksii.2018.19.5.89

Cluster and Polarity Analysis of Online Discussion Communities Using User Bipartite Graph Model  

Kim, Sung-Hwan (Department of Electrical and Computer Engineering, Pusan Nation al University)
Tak, Haesung (Department of Electrical and Computer Engineering, Pusan Nation al University)
Cho, Hwan-Gue (Department of Electrical and Computer Engineering, Pusan Nation al University)
Publication Information
Journal of Internet Computing and Services / v.19, no.5, 2018 , pp. 89-96 More about this Journal
Abstract
In online communities, a large number of participants can exchange their opinion using replies without time and space restrictions. While the online space provides quick and free communication, it also easily triggers unnecessary quarrels and conflicts. The network established on the discussion participants is an important cue to analyze the confrontation and predict serious disputes. In this paper, we present a quantitative measure for polarity observed on the discussion network built from reply exchanges in online communities. The proposed method uses the comment exchange information to establish the user interaction network graph, computes its maximum spanning tree, and then performs vertex coloring to assign two colors to each node in order to divide the discussion participants into two subsets. Using the proportion of the comment exchanges across the partitioned user subsets, we compute the polarity measure, and quantify how discussion participants are bipolarized. Using experimental results, we demonstrate the effectiveness of our method for detecting polarization and show participants of a specific discussion subject tend to be divided into two camps when they debate.
Keywords
Internet Community; Online Discussion; Reply Tree; Bipartite Graph; Social Network;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 N. Zhao, and X. Liu, "Information Propagation in Social Networks with Overlapping Community Structure," KSII Transactions on Internet and Information Systems, Vol. 11, No. 12, pp. 5927-5942, 2017. http://dx.doi.org/10.3837/tiis.2017.12.013   DOI
2 C.-G. Han, and M.-H. Jo, "An Enhanced Community Detection Algorithm Using Modularity in Large Networks," Journal of Internet Computing and Services, Vol. 13, No. 3, pp. 75-82, 2012. http://dx.doi.org/10.7472/jksii.2012.13.3.75   DOI
3 A. J. Morales, J. Borondo, J. C. Losada, and R. M. Benito, "Measuring Political Polarization: Twitter Shows the Two Sides of Venezuela," Chaos, Vol 25, No 033114, 2015. http://dx.doi.org/10.1063/1.4913758
4 S. Rosenthal, and K. McKeown, "Couldn't Agree More: The Role of Conversational Structure in Agreement and Disagreement Detection in Online Discussions," in Proc. SIGDIAL, pp. 168-177, 2015. http://dx.doi.org/10.18653/v1/W15-4625   DOI
5 K .Beelen, E. Kanoulas, and B. van de Velde, "Detecting Controversies in Online News Media," in Proc. ACM SIGIR, pp. 1069-1072, 2017. http://dx.doi.org/10.1145/3077136.3080723   DOI
6 V. Gomez, V. Kaltenbrunner and V. Lopez, "Statistical Analysis of the Social Network and Discussion Threads in Slashdot," in Proc. WWW, pp.645-654, 2008. http://dx.doi.org/10.1145/1367497.1367585   DOI
7 T. C. Li, J. Gharibshah, E. E. Papalexakis, and M. Faloutsos, "Trollspot: Detecting Misbehavior in Commenting Platforms," in Proc. ASONAM, pp.171-175, 2017. http://dx.doi.org/10.1145/3110025.3110057   DOI
8 M. Lee, I. Choi, and S. Yang, "When Do People Post a Comment to a News Story on the Internet?," KSII Transactions on Internet and Information Systems, Vol. 6, No. 1, pp. 434-445, 2015. http://dx.doi.org/10.3837/tiis.2015.01.027
9 M. Yannakakis, "Node- and Edge-deletion NP-complete problems," in Proc. STOC, pp.253-264, 1978. http://dx.doi.org/10.1145/800133.804355   DOI
10 R. Peeters, "The Maximum Edge Biclique Problem is NP-complete," Discrete Applied Mathematics, Vol. 131, No. 3, pp. 651-654, 2003. http://dx.doi.org/10.1016/S0166-218X(03)00333-0   DOI