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New Technology of Library and Information Service  2015, Vol. 31 Issue (6): 71-77    DOI: 10.11925/infotech.1003-3513.2015.06.11
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Feature Recognition of Niche Expert——Empirical Analysis Based on MetaFilter Dataset
Li Gang, Ye Guanghui, Zhang Yan
Center for the Studies of Information Resources, Wuhan University, Wuhan 430072, China
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[Objective] In order to fully get expert resource, this paper explores the feature recognition method of niche expert. [Methods] Firstly, take advantage of user activity data from a famous community weblog named MetaFilter to construct user interaction network. Secondly, make statistics of node network structure indexes, such as betweenness centrality, clustering coefficient. Finally, feature and role of node in different period is distinguished via the combination of cluster analysis and time series analysis. [Results] This paper obtains the niche expert collection through comparative analysis of network statistics indexes of different clusters, the classification of niche experts are further refined based on temporal changes in the collection. [Limitations] Role identification and migration analysis should be expanded to more sections, not only the music section, so that the “stability-change” feature of niche experts under different semantic circumstance can be further discussed. [Conclusions] Niche expert is an effective supplement to the existing collection of experts, the method proposed in this paper can be applied to many aspects, such as the construction of expert team, the recommendations and retrieval of experts, and so on.

Key wordsNiche expert      Feature recognition      Social semantic network      Clustering analysis      Role migration     
Received: 17 November 2014      Published: 08 July 2015
:  G350  

Cite this article:

Li Gang, Ye Guanghui, Zhang Yan. Feature Recognition of Niche Expert——Empirical Analysis Based on MetaFilter Dataset. New Technology of Library and Information Service, 2015, 31(6): 71-77.

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