NDLI: OOLAM: an opinion oriented link analysis model for influence persona discovery

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OOLAM: an opinion oriented link analysis model for influence persona discovery

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OOLAM: an opinion oriented link analysis model for influence persona discovery

Content Provider	ACM Digital Library
Author	Ma, Rui Zhang, Li Yang, Zi Cai, Keke Tang, Jie Bao, Shenghua Su, Zhong
Abstract	Social influence is a complex and subtle force that governs the dynamics of social networks. In the past years, a lot of research work has been conducted to understand the spread patterns of social influence. However, most of approaches assume that influence exists between users with active social interactions, but ignore the question of what kind of influence happens between them. As such one interesting and also fundamental question is raised here: "in a social network, could the social connection reflect users'influence from both positive and negative aspects?". To this end, an Opinion Oriented Link Analysis Model (OOLAM) is proposed in this paper to characterize users' influence personae in order to exhibit their distinguishing influence ability in the social network. In particular, three types of influence personae are generalized and the problem of influence persona discovery is formally defined. Within the OOLAM model, two factors, i.e., opinion consistency and opinion creditability, are defined to capture the persona information from public opinion perspective. Extensive experimental studies have been performed to demonstrate the effectiveness of the proposed approach on influence persona analysis using real web data sets.
Starting Page	645
Ending Page	654
Page Count	10
File Format	PDF
ISBN	9781450304931
DOI	10.1145/1935826.1935915
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-02-09
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Link analysis Opinion consistency Creditability analysis Influence persona discovery
Content Type	Text
Resource Type	Article

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