Detecting changes of opinion from customer reviews

With the flourishing of the world wide web, the online customer review process is becoming more and more useful and important as an information resource for people. As a result, opinion mining research for analysis of opinion data on the web has recently become a popular topic. Most previous studies...

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Bibliographische Detailangaben
Hauptverfasser: Li-Chen Cheng, Zhi-Han Ke, Bang-Min Shiue
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:With the flourishing of the world wide web, the online customer review process is becoming more and more useful and important as an information resource for people. As a result, opinion mining research for analysis of opinion data on the web has recently become a popular topic. Most previous studies have used Pointwise Mutual Information (PMI) to predict the opinion (positive or negative). This study first proposes a method which combines the associative classification methodology with the overall rating to discover the relation of the features. By the way, a framework is also proposed to discover those changes of opinion that can identify the users' opinion of a product. Experimental results, in mining ipad review information, demonstrate the effectiveness of the proposed approach. The data set used contains actual WOM information from which to study the dynamic patterns of users' changing opinions. The summarized results can help consumers and marketing managers to make decision.
DOI:10.1109/FSKD.2011.6019917