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Communities of Yahoo! Answers and Baidu Zhidao: Complementing or competing?

Authors: Baichuan Li; Michael R. Lyu; Irwin King;

Communities of Yahoo! Answers and Baidu Zhidao: Complementing or competing?

Abstract

Community Question Answering (CQA) attracts increasing volume of research on question retrieval, high quality content discovery and experts finding. However, few studies are focused on community per se of CQA services and also provide an in-depth analysis of them. This paper aims to enrich our knowledge on two of these CQA services, namely Yahoo! Answers and Baidu Zhidao through reviewing their communities, comparing similarities and differences of the two communities, together with analyzing their influence on solving questions. Six data sets are employed for comparative analysis. In this paper: (1) We analyze the social network structures of Yahoo! Answers and Baidu Zhidao; (2) We compare the the social community characteristics of top contributors; (3) We reveal the behaviors of users in different categories in these two portals; (4) We reveal temporal trends of these characteristics; (5) We find that the community of Yahoo! Answers and Baidu Zhidao complement each other in efficiency and effectiveness of answering questions.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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