Event-Based User Classification in Weibo Media

Weibo media, known as the real-time microblogging services, has attracted massive attention and support from social network users. Weibo platform offers an opportunity for people to access information and changes the way people acquire and disseminate information significantly. Meanwhile, it enables...

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Main Authors: Liang Guo, Wendong Wang, Shiduan Cheng, Xirong Que
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/479872
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author Liang Guo
Wendong Wang
Shiduan Cheng
Xirong Que
author_facet Liang Guo
Wendong Wang
Shiduan Cheng
Xirong Que
author_sort Liang Guo
collection DOAJ
description Weibo media, known as the real-time microblogging services, has attracted massive attention and support from social network users. Weibo platform offers an opportunity for people to access information and changes the way people acquire and disseminate information significantly. Meanwhile, it enables people to respond to the social events in a more convenient way. Much of the information in Weibo media is related to some events. Users who post different contents, and exert different behavior or attitude may lead to different contribution to the specific event. Therefore, classifying the large amount of uncategorized social circles generated in Weibo media automatically from the perspective of events has been a promising task. Under this circumstance, in order to effectively organize and manage the huge amounts of users, thereby further managing their contents, we address the task of user classification in a more granular, event-based approach in this paper. By analyzing real data collected from Sina Weibo, we investigate the Weibo properties and utilize both content information and social network information to classify the numerous users into four primary groups: celebrities, organizations/media accounts, grassroots stars, and ordinary individuals. The experiments results show that our method identifies the user categories accurately.
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institution Kabale University
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publishDate 2014-01-01
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record_format Article
series The Scientific World Journal
spelling doaj-art-f1984e78c7f74bf4bf639b5e525408e72025-02-03T01:29:23ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/479872479872Event-Based User Classification in Weibo MediaLiang Guo0Wendong Wang1Shiduan Cheng2Xirong Que3State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaWeibo media, known as the real-time microblogging services, has attracted massive attention and support from social network users. Weibo platform offers an opportunity for people to access information and changes the way people acquire and disseminate information significantly. Meanwhile, it enables people to respond to the social events in a more convenient way. Much of the information in Weibo media is related to some events. Users who post different contents, and exert different behavior or attitude may lead to different contribution to the specific event. Therefore, classifying the large amount of uncategorized social circles generated in Weibo media automatically from the perspective of events has been a promising task. Under this circumstance, in order to effectively organize and manage the huge amounts of users, thereby further managing their contents, we address the task of user classification in a more granular, event-based approach in this paper. By analyzing real data collected from Sina Weibo, we investigate the Weibo properties and utilize both content information and social network information to classify the numerous users into four primary groups: celebrities, organizations/media accounts, grassroots stars, and ordinary individuals. The experiments results show that our method identifies the user categories accurately.http://dx.doi.org/10.1155/2014/479872
spellingShingle Liang Guo
Wendong Wang
Shiduan Cheng
Xirong Que
Event-Based User Classification in Weibo Media
The Scientific World Journal
title Event-Based User Classification in Weibo Media
title_full Event-Based User Classification in Weibo Media
title_fullStr Event-Based User Classification in Weibo Media
title_full_unstemmed Event-Based User Classification in Weibo Media
title_short Event-Based User Classification in Weibo Media
title_sort event based user classification in weibo media
url http://dx.doi.org/10.1155/2014/479872
work_keys_str_mv AT liangguo eventbaseduserclassificationinweibomedia
AT wendongwang eventbaseduserclassificationinweibomedia
AT shiduancheng eventbaseduserclassificationinweibomedia
AT xirongque eventbaseduserclassificationinweibomedia