Meihui Chen

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Meihui Chen is an author.


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Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Monitoring propagations in the blogosphere for viral marketing Blogs
Content based propagation
Page return of search engine
Text mining
Viral marketing
Journal of Emerging Technologies in Web Intelligence English 2012 Even though blog contents vary a lot in quality, the disclosure of personal opinions and the huge blogging population always attracts marketing..s attention on blog information. In this paper, we investigate how marketers can identify the information propagation in degree among blog communities. In this way, topic similarity, relatedness, and word repetition between leader and followers.. writing products are considered as the propagated information. The contribution of this paper is twofold. The work presented here is to show how blog content can be economically and feasibly analyzed by existing internet sources such as Wikipedia database and the usage of page return from a Japanese search engine. To this extent, this system, which combined in-link algorithms and text mining analyzes, tracing propagation channels and propagateable information allows analyzing the power of influences in viral marketing. We demonstrated the effectiveness of the system by applying blogger identification, topic identification, and the topic propagations. 0 0
Testing an Integrative Theoretical Model of Knowledge-Sharing Behavior in the Context of Wikipedia Journal of the American Society for Information Science and Technology 2010 This study explores how and why people participate in collaborative knowledge-building practices in the context of Wikipedia. Based on a survey of 223 Wikipedians, this study examines the relationship between motivations, internal cognitive beliefs, social-relational factors, and knowledge-sharing intentions. Results from structural equation modeling {(SEM)} analysis reveal that attitudes, knowledge self-efficacy, and a basic norm of generalized reciprocity have significant and direct relationships with knowledge-sharing intentions. Altruism (an intrinsic motivator) is positively related to attitudes toward knowledge sharing, whereas reputation (an extrinsic motivator) is not a significant predictor of attitude. The study also reveals that a social-relational factor, namely, a sense of belonging, is related to knowledge-sharing intentions indirectly through different motivational and social factors such as altruism, subjective norms, knowledge self-efficacy, and generalized reciprocity. Implications for future research and practice are discussed. 0 1