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An Empirical Study on IWOM Monitoring and Evaluation of Public Opinion Based on Fuzzy Inference of Affective Membership Degree——A Case Study of Online Reviews on the Mobile Phone Brand
Received date: 2016-09-02
Revised date: 2016-11-16
Online published: 2016-12-05
[Purpose/significance] According to Chinese customer reviews on the Internet, grabbing online reviews information from network platform with consumers' real-word experience,this paper builds online sentiment membership IWOM monitoring and evaluation model and system based on fuzzy inference to help enterprise monitor real-time IWOM. [Method/process] Based on the U.S. consumer satisfaction model (ACSI), model of online reputation monitoring and evaluation is built from the aspects of perceived quality, perceived value, perceived expectations and perception of emotional four attributes. Combined with the emotion fuzzy reasoning algorithm from data preparation,emotion analysis and word-of-mouth network public opinion monitoring and evaluation three study phases, by setting the fuzzy inference system calculation rules, it uses Mamdani method to monitor and evaluate word-of-mouth network public opinion. [Result/conclusion] Taking mobile phone brand online reviews on Amazon as an example, network public opinion monitoring and evaluation method based on fuzzy inference of affective membership degree obtains good results of experiment test, which can provide information for decision-making of network public opinion monitoring and evaluation of online product.
Zhang Yanfeng , Li He , Peng Lihui , Chen Yuanfang . An Empirical Study on IWOM Monitoring and Evaluation of Public Opinion Based on Fuzzy Inference of Affective Membership Degree——A Case Study of Online Reviews on the Mobile Phone Brand[J]. Library and Information Service, 2016 , 60(23) : 119 -127 . DOI: 10.13266/j.issn.0252-3116.2016.23.015
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