Computer Science ›› 2020, Vol. 47 ›› Issue (11A): 430-436.doi: 10.11896/jsjkx.200500024

• Big Data & Data Science • Previous Articles     Next Articles

User Importance Evaluation for Q&A Platform Based on User Relations

LI Xiao, QU Yang, LI Hui, GUO Shi-kai   

  1. Information Science and Technology College,Dalian Maritime University,Dalian,Liaoning 116026,China
  • Online:2020-11-15 Published:2020-11-17
  • About author:LI Xiao,born in 1994,postgraduate student.His main research interests include mining software repository and so on.
    LI Hui,born in 1983,Ph.D,associate professor,master supervisor,is a member of China Computer Federation.His main research interests include mining software repository,and complex networks.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (61602077,61902050),Fellowship of China Postdoctoral Science Foundation(2020M670736),Fundamental Research Funds for the Central Universities (3132019355) and Next-Generation Internet Innovation Project of CERNET (NGII20181205,NGII20190627).

Abstract: Q&A has increasingly become an important platform of acquiring knowledge for WWW users.As the number of the users rapidly increases,the identification of the important users becomes more and more difficult,and more and more questions cannot be answered in Q&A platforms.Thus it seriously affects the user experience.Aiming to solve this problem,we regard the questions and answers of users in the Q&A platform as a kind of social network behavior,and build a user relationship network based on these behaviors.On this basis,we present an evaluation of user importance ranking based on the user relationship network,and further identify the important users of the platforms.Experimental studies based on data set of Stack Overflow show that,the results produced by the user important ranking is consistent with the actual ranking lists,and the produced ranking results are relatively stable.Furthermore,the ranking results can be used for improving the question recommendation.Applying the user importance ranking measurement,we designed and developed a Q&A platform.Empirical studies show that this ranking method can identify the important users from Q&A platform,and improve the user experience of knowledge acquirement.

Key words: Q&A platform, Question recommendation, Social network, User importance ranking

CLC Number: 

  • TP393
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