Meng Meiren, Ding Shengchun
This paper aims at filtering the lower credible online Chinese product reviews to offer valuable reviews for consumers’ purchase decision. Based on the deep analysis of the online Chinese product reviews’ characteristics, also with some related works, the authors make an empirical analysis on the credibility factors through questionnaires. According to the results of the empirical analysis, the authors select content integrity, emotional balance, review timeliness and clarity of the identity of the publisher as four features, use CRFs as reviews credibility’s classification model, and conduct feature combination experiments to get the best feature combination. The experiments achieve significant results, and the correct rates of the classification model are all above 75%. The research results of this paper can improve the existing artificial effectiveness evaluation method, thus offering new methods and thoughts for optimized filtering of the online reviews.
