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Using dynamic community detection to identify trends in user-generated content

In this paper, we present a new solution for trend detection in user-generated content, and more particularly Web 2.0 social networks. Whereas some propositions have been published in this domain recently, we have chosen a new approach based on network analysis. We first create an evolving network o...

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Published in:Social network analysis and mining 2012-12, Vol.2 (4), p.361-371
Main Authors: Cazabet, Rémy, Takeda, Hideaki, Hamasaki, Masahiro, Amblard, Frédéric
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Language:English
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cited_by cdi_FETCH-LOGICAL-c312t-893918e82196fb0eb79cc3d2263e2036870c84f0515d88b579b2f71713718b603
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creator Cazabet, Rémy
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description In this paper, we present a new solution for trend detection in user-generated content, and more particularly Web 2.0 social networks. Whereas some propositions have been published in this domain recently, we have chosen a new approach based on network analysis. We first create an evolving network of terms, which is an abstraction of the complete network, and then run a dynamic community detection algorithm on this evolving network. In order to be able to detect not only short, bursting events, but also more persistent topics, we test our solution on a social network for which we have information about all published contents for a period of more than 2 years: the Japanese network Nico Nico Douga. After presenting our solution in detail, we present the results on this dataset, notably a statistical analysis of communities’ sizes and durations, examples of detected communities, and a typology of the different kinds of trends detected. Finally, we discuss the advantages and disadvantages of this method, as well as its possible applications.
doi_str_mv 10.1007/s13278-012-0074-8
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source International Bibliography of the Social Sciences (IBSS); Social Science Premium Collection; Springer Nature
subjects Algorithms
Applications of Graph Theory and Complex Networks
Community
Computer Science
Data Mining and Knowledge Discovery
Datasets
Economics
Evolution
Game Theory
Humanities
Keywords
Law
Methodology of the Social Sciences
Methods
Network analysis
Ontology
Original Article
Soccer
Social and Behav. Sciences
Social networks
Statistical analysis
Statistics for Social Sciences
Tagging
Trends
User generated content
Web 2.0
title Using dynamic community detection to identify trends in user-generated content
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