Translated Titles

Quality Classification of Word of Mouth Based on an Information Quality Framework



Key Words

支援向量機 ; 資訊品質 ; 口碑分類 ; 層級分析程序法 ; 意見探勘 ; Information Quality ; Opinion Mining ; Support Vector Machine ; Word of Mouth Classification ; Analytic Hierarchy Process



Volume or Term/Year and Month of Publication


Academic Degree Category




Content Language


Chinese Abstract


English Abstract

WOM (word-of-mouth) has become important reference sources for consumers. They consider others’ experiences and suggestions before making purchase decisions. There are a lot of WOM be written by reviewers on the Internet. These reviewers’ writing styles are without any restrictions. For this reason, lead to difficult for consumers to find useful and qualitative information. In literature, most WOM mining researches mainly focus on document sentimental classification but ignore the importance of WOM quality. In this research, we classify WOM documents based on the information quality (IQ) framework. In the part of sentiment, we determine polarity of sentimental term with sentimental values of SentiWordNet in order to automatically identify the opinion sentences in a document. Furthermore, different elements of IQ may have different influencing power on quality. Therefore, this research extracts experts’ opinions and evaluates importance degree of IQ elements through the analytic hierarchy process (AHP). Experiment results show that our proposed approach which integrates IQ framework with AHP technique can promote performance on WOM quality classification and also demonstrate that different IQ elements have different importance on information quality.

Topic Category 商學院 > 資訊管理研究所
社會科學 > 管理學
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