A Framework for Discovering Opinions on Issues From User Generated Content: Using Cross-Strait Agreement on Trade in Services as an Example

• Main Authors: Bo-Chih Liu, 劉鉑志
• Other Authors: S.Y. Hwang
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/ggbrum

碩士 === 國立中山大學 === 資訊管理學系研究所 === 102 === User generated content (UGC) is increasing quickly due to the advance of information technology. A post about enterprise finance condition or social political issue in forums is part of UGC. Nowadays applying text mining and sentiment analysis techniques on UGC has been shown to be a promising alternative to the traditional polls. In this work, we propose a framework for discovering opinions on issues discussed on forums, specifically those related to Cross-Strait Agreement on Trade in Services. In particular, we identify issues by finding frequent nouns and then discover the pertaining opinions on the posts. Over Fifteen thousand posts on PTT forums are processed using the proposed approach. Finally, we discover that the overall emotion on various issues tend to be negative, whereas the amount of discussion and the degree of negative emotions vary dramatically.