Frontiers of Data and Domputing ›› 2021, Vol. 3 ›› Issue (4): 126-139.doi: 10.11871/jfdc.issn.2096-742X.2021.04.011

• Technology and Applicaton • Previous Articles     Next Articles

A Method of Opinion Leader Discovery Based on Comprehensive Influence and Sentiment Characteristics

WANG Jiaqi1,2(),DU Yihua1,*(),ZHAO Yixia1()   

  1. 1. Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2021-02-22 Online:2021-08-20 Published:2021-08-30
  • Contact: DU Yihua E-mail:wangjiaqi@cnic.cn;yhdu@cashq.ac.cn;zyx@cnic.cn

Abstract:

[Objective] In response to the phenomenon that traditional opinion leader discovery methods are limited to partial data features and lead to ignoring of some opinion leaders, this paper proposes a new opinion leader discovery method called CI-SC to achieve the purpose of discovering the ignored opinion leaders. [Methods] CI-SC integrates the influence characteristics of users in both profile attributes and post interaction behaviors to build a comprehensive influence evaluation index. By introducing users' sentiment characteristics, CI-SC achieves the discovery of opinion leaders through cluster analysis based on the above characteristics. The results are evaluated by analyzing identity information and social connections. [Results] According to the experimental results, the opinion leaders found by our method have higher statistical significance and lower overlap ratio compared with those found by traditional methods, which means that by considering more aspects of information, our method can effectively identify opinion leaders with greater influence and obvious sentiment characteristics that are ignored by traditional methods. [Limitations] The proposed method has only been tested on a small dataset so far. Thus, more experiments on larger datasets are needed to further validate its effectiveness. [Conclusions] This paper proposed a new opinion leader discovery method called CI-SC, which is based on comprehensive influence and sentiment characteristics. Experimental results prove that by taking into account the influence of a user in different aspects and further combining the influence with the sentiment characteristics, CI-SC improves the traditional opinion leader discovery methods in discovering opinion leaders without neglecting some information. Therefore, our method can be an effective supplement to traditional methods and has practical value in opinion analysis and guidance.

Key words: electronic invoice, block chain, duplicate reimbursement, information immutability, CI-SC, influence, sentiment polarity, opinion leader discovery