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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/75022

Title:	Discovering political tendency in bulletin board discussions by social community analysis
Authors:	Lee, K.-C.;Shan, Mankwan 沈錳坤
Contributors:	資科系
Keywords:	Bulletin board systems;Discussion boards;Graph clustering;Graph colorings;Graph partition;Linguistic analysis;Social communities;Social interactions;Social Networks;Clustering algorithms;Information management;Bulletin boards
Date:	2009-12
Issue Date:	2015-05-07 15:28:24 (UTC+8)
Abstract:	Bulletin Board System (BBS) is very popular and provide an asynchronous, text-based environment for users to exchange information and idea. A BBS consists of a number of discussion boards, each of which focuses on a particular subject. A discussion on a topic consists of a seed articles followed by some articles responsive to the seed article or other responsive articles. This paper investigates the social community analysis technique to discover the political tendency of users within the boards from discussions. We first extract the social interactions between users, such as "reply" and "advocate" ofposts between users. A social network among users is constructed based on the extracted social interaction. After building the social network, we employ the graph partition, graph coloring, and graph clustering algorithms respectively to discover the social communities. Users of the same community have more potential of political opinion agreement with each other. By using this approach, we are able to partition users into two opposite groups and identify their political tendency effectively without linguistic analysis of discussion content. © 2009 IEEE.
Relation:	4th International Conference on Digital Information Management, ICDIM 2009,1-5
Data Type:	conference
DOI link:	http://dx.doi.org/10.1109/ICDIM.2009.5356800
DOI:	10.1109/ICDIM.2009.5356800
Appears in Collections:	[Department of Computer Science ] Proceedings

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