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Abstract:
Existing models for measuring user social influence fail to integrate both opinion and topic information. Therefore, a new constrained nonnegative tensor factorization method combining user's opinion and the topical relevance was proposed. The method represented user's comment relations as 3-order tensor, factorized the comments tensor constrained by Laplacian topical matrix, and then measures user influence according to the latent factors resulting from the tensor factorization. Thus, the new method not only was capable to effectively calculate the strength of user social influence on given topic, but also kept the polarity allocation of social influence. The experimental result shows that the performance of the proposed method is better than that of the baseline methods such as OOLAM, TwitterRank, etc. © 2016, Editorial Board of Journal on Communications. All right reserved.
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Journal on Communications
ISSN: 1000-436X
CN: 11-2102/TN
Year: 2016
Issue: 6
Volume: 37
Page: 154-162
Cited Count:
SCOPUS Cited Count: 3
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 4
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