An Effective Approach to Finding a Context Path in Review Texts Using Pathfinder Scaling

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• 关键词：Content analysis ; Context structure ; Context path ; Pathfinder network (PFNet) ; Review mining
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：10046
• 期：1
• 页码：376-388
• 全文大小：1,295 KB
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• 作者单位：Erin Hea-Jin Kim (15)
  SuYeon Kim (15)
  
  15. Department of Library and Information Science, Yonsei University, Seoul, Korea
  
• 丛书名：Social Informatics
• ISBN：978-3-319-47880-7
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：10046

文摘

Customer reviews feature opinions or sentiments that a review writer has given, and these opinions or sentiments have an impact on the reader. Identifying and presenting word associations that indicate a sentiment orientation and semantics can aid in selecting the best review for providing the information customers are seeking. In this paper, we attempted to discover the context structure and the context path presenting explicit semantics in review texts. To this end, we extracted word co-occurrences and converted them to a cosine adjacency matrix. Then a co-word network applied by Pathfinder scaling was constructed. Finally, we measured the context score and presented context paths from the context structure in the review texts. In results, our approach found that a compound noun is easy to detect by network analysis. The extracted context paths remain intact, a sentiment polarity derived from review texts. The evaluative expression for a certain aspect of a product or service is clearer and more specified within the context path. Furthermore, it is not necessary to train reference words to detect the sentiment orientations.