建立在資訊品質架構上的口碑文章品質分類

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

黃馨儀

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

中原大學資訊管理研究所學位論文

2011年

碩士

洪智力

繁體中文

口碑對消費者來說已經成為重要的參考依據。他們在做購買決策之前，會考慮其他消費者的經驗與建議。但是現在網際網路中有著大量的口碑資訊，加上評論者撰寫口碑文章的方式是沒有任何限制，導致消費者很難從眾多品質不一的文章中找到有用的資訊。在文獻中，大部分的口碑探勘研究主要都重視在文章情感的分類，卻忽略了口碑品質的重要性。本研究以資訊品質(IQ)架構為基礎來分類口碑文章，其中情感判斷方面，本研究採用SentiWordNet提供的情感值來判斷情感詞彙的傾向，進而自動化的辨識出文章中之意見句子。除此之外，不同的資訊品質因素在品質上可能有不同的影響力。因此，本研究萃取專家意見並透過層級分析程序法(AHP)來評估資訊品質因素的重要程度，再使用重要程度值加權資訊品質因素，使得資訊品質因素特徵值之間的差異更大。實驗結果顯示，本研究提出層級分析程序法技術整合資訊品質架構的方法能有效提升口碑品質分類的效果，也證實資訊品質當中不同的資訊品質因素具有不同的重要性。

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.

1.  Cao, L.J. and Tay, F.E.H. (2003). Support Vector Machine with Adaptive Parameters in Financial Time Series Forecasting. IEEE Transactions on Neural Networks, Vol. 14, pp.1506-1518.
   連結：
2.  Chevalier, J. A. and Mayzlin, D. (2006). The effect of word of mouth on sales: online book reviews. Journal of Marketing Research, Vol.43, No.3, pp. 345-354.
   連結：
3.  DeLone, W. H., and McLean, E. R. (1992). Information System Success: The Quest for the Dependent Variable. Information System Research, Vol.3, No.1, pp. 60-95.
   連結：
4.  Fellbaum, C. editor (1998). WordNet: An Electronic Lexical Database. MIT Press.
   連結：
5.  Ghose, A. and Ipeirotis, P. G. (2007). Designing Novel Review Ranking Systems: Predicting the Usefulness and Impact of Reviews. Proceedings of the 9th International Conference on Electronic Commerce (ICEC), pp. 303-310.
   連結：
6.  Godes, D., Mayzlin, D. (2004). Using online conversations to study word-of-mouth communication, Marketing Science, Vol.23, No.4, pp. 545-560.
   連結：
7.  Luhn, H. P. (1958). The Automatic Creation of Literature Abstracts. IBM Journal of Research and Development, Vol. 2, pp.157-165.
   連結：
8.  McKinney, V., Yoon, K., and Zahedi, F. M. (2002). The Measurement of Web-Customer Satisfaction: An Expectation and Disconfirmation Approach. Information Systems Research, Vol. 13, No. 3, pp. 296-315.
   連結：
9.  Saaty, T. L. (1980). The Analytic Hierarchy Process. McGraw-Hill, New York.
   連結：
10.  Saaty, T. L. (1990). How to Make a Decision: The Analytic Hierarchy Process. European Journal of Operational Research, Vol. 48, pp. 9-26.
    連結：
11.  Saaty, T. L. (2002). Decision Making with the Analytic Hierarchy Process. Scientia Iranica, Vol. 9, No. 3, pp.215-229.
    連結：
12.  Saaty, T. L. (2004). Decision Making-The Analytic Hierarchy and Network Processes (AHP/ANP). Journal of Systems Science and Systems Engineering, Vol. 13, No. 1, pp.1-34.
    連結：
13.  Saaty, T. L. (2008). Decision Making with the Analytic Hierarchy Process. Int. J. Services Sciences, Vol. 1, No. 1, pp.83-98.
    連結：
14.  Seki, Y., Evans, D. K., Ku, L. W., Chen, H. H., Kando, N. and Lin, C. Y. (2007). Overview of Opinion Analysis Pilot Task at NTCIR-6. Proceedings of the Workshop Meeting of the National Institute of Informatics (NII) Test Collection for Information Retrieval Systems (NTCIR), pp. 265-278.
    連結：
15.  Song, J. and Zahedi, F. M. (2007). Trust in Health Infomediaries. Decision Support Systems, Vol. 43, pp. 390-407.
    連結：
16.  Wang, R.Y., Strong, D.M. (1996). Beyond Accuracy: What Data Quality Means to Data Consumers. Journal of Management Information Systems, Vol. 12, No.4, pp.5-33.
    連結：
17.  Xu, J. R., Zhang, J. X., Han, B. C., Liang, L. and Ji, Z. L. (2007). CytoSVM: An Advanced Server for Identification of Cytokine-receptor Interactions. Nucleic Acids Res, Vol. 35, pp. W538-542.
    連結：
18.  Yu, X., Liu, Y., Huangy, X. and An, A. (2010). A Quality-Aware Model for Sales Prediction Using Reviews. Proceedings of the 19th International Conference on World Wide Web, pp. 1217-1218.
    連結：
19.  林晏僖、高照明與高成炎(2008)，中文名詞組的辨識：監督式與半監督式學習法的實驗，自然語言與語音處理研討會(ACL)。
    連結：
20.  Benamara, F., Cesarano, C., Picariello, A., Reforgiato, D. and Subrahmanian, V. S. (2007). Sentiment Analysis: Adjectives and Adverbs are better than Adjectives Alone. Proceedings of the International Conference on Weblogs and Social Media (ICWSM).
21.  Brill, E. (1992). A Simple Rule-Based Part of Speech Tagger. Proceedings of the Third Conference on Applied Computational Linguistics (ACL), Trento, Italy.
22.  Esuli, A. and Sebastiani, F. (2006). SentiWordNet: A Publicly Available Lexical Resource for Opinion Mining. Proceedings of Language Resources and Evaluation (LREC).
23.  Gamon, M., Aue, A., Corston-Oliver, S. and Ringger, E. (2005). Pulse: Mining Customer Opinions from Free Text. Proceedings of the International Symposium on Intelligent Data Analysis (IDA), pp.121-132.
24.  Ghose, A., Ipeirotis, P.G and Sundararajan, A. (2007). Opinion Mining Using Econometrics: A Case Study on Reputation Systems. Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, Prague, Czech Republic, pp. 416–423.
25.  Hatzivassiloglou, V. and McKeown, K. R. (1997). Predicting the Semantic Orientation of Adjectives. Proceedings of the 8th conference on European chapter of the Association for Computational Linguistics.
26.  Hu, M. and Liu, B. (2004). Mining and Summarizing Customer Reviews. Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 168-177.
27.  Jindal, N. and Liu, B. (2008). Opinion Spam and Analysis. Proceedings of the International Conference on Web Search and Web Data Mining, pp. 219-230.
28.  Kelton, K., Fleischmann, K. R. and Wallace, W. A. (2008). Trust in Digital Information. Journal of the American Society for Information Science and Technology, Vol. 59, No. 3, pp. 363-374.
29.  Kim, S.M., Pantel, P., Chklovski, T., Pennacchiotti, M. (2006). Automatically Assessing Review Helpfulness. Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 423-430.
30.  Liu, J., Cao, Y., Lin, C.Y., Huang, Y., Zhou, M. (2007a). Low-Quality Product Review Detection in Opinion Summarization. Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), pp. 334–342.
31.  Liu, Y., Huang, X., An, A. and Yu, X. (2008). Helpmeter: A Nonlinear Model for Predicting the Helpfulness of Online Reviews. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), Vol. 1, pp. 793-796.
32.  Liu,Y., Huang, X., An, A. and Yu, X. (2007b). ARSA: A Sentiment-Aware Model for Predicting Sales Performance Using Blogs. Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 607-614.
33.  Pang, B., Lee, L. and Vaithyanathan, S. (2002). Thumbs Up? Sentiment Classification Using Machine Learning Techniques. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 79-86.
34.  Seki, Y., Eguchi, K., Kando, N. and Aono, M. (2006). Opinion-Focused Summarization and Its Analysis at DUC 2006. Proceedings of the Document Understanding Conference (DUC), pp. 122-130.
35.  Seki, Y., Evans, D. K., Ku, L.-W., Sun, L., Chen, H.-H. and Kando, N. (2008). Overview of Multilingual Opinion Analysis Task at NTCIR-7. Proceedings of the 7th NTCIR Workshop Meeting, Tokyo Japan, pp. 16-19.
36.  Somasundaran, S., Ruppenhofer, J. and Wiebe, J. (2007). Detecting Arguing and Sentiment in Meetings. Proceedings of the 8th SIGdial Workshop on Discourse and Dialogue.
37.  Tseng, Y.-D. and Chen, C. C. (2009). Using an Information Quality Framework to Evaluate the Quality of Product Reviews. Proceedings of the 5th Asia Information Retrieval Symposium on Information Retrieval Technology, pp. 100-111.
38.  Turney, P.D. (2002). Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews. Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL), pp 417-424.
39.  Valitutti, A., Strapparava, C. and Stock, O. (2004). Developing affective lexical resources. PsychNology Journal, Vol.2, No.1, pp.61-83.
40.  Vapnik, V. N. (2000). The Nature of Statistical Learning Theory. Statistics for Engineering and Information Science, 2nd ed., Springer-Verlag New York Inc.
41.  Weimer, M. and Gurevych, I. (2007). Predicting the Perceived Quality of Web Forum Posts. Proceedings of the Conference on Recent Advances in Natural Language Processing.
42.  Yu, H. (2010). Using Learning Classifier to Recognize Face Image. 2010 2nd International Conference on Advanced Computer Control (ICACC), Vol. 2, pp. 523-526.
43.  Zhang, Z., Varadarajan, B. (2006). Utility Scoring of Product Reviews. Proceedings of the 15th ACM International Conference on Information and Knowledge Management, pp. 51-57.
44.  Zhuang, L., Jing, F., Zhu, X. Y. and Zhang, L. (2006). Movie Review Mining and Summarization. Proceedings of the ACM SIGIR Conference on Information and Knowledge Management (CIKM).
45.  Alexa中文資訊站(2010)，http://www.alexacn.org/alexasjpm.html。
46.  周立柱、賀宇凱和王建勇(2008)，情感分析研究綜述，計算機應用，第28卷，第11期，11月。