Text Mining and Sentiment Analysis for the Application of the Product Recommendation-The Case of PTT Movie Board

• Main Authors: Zhang, Chuan-Heng, 張傳珩
• Other Authors: Huang, Jih-Jeng
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/62w2x2

碩士 === 東吳大學 === 資訊管理學系 === 107 === Thanks to internet technology improvements and the smart devices popularized, we can find a huge variety of information and different kind of social media platforms. Nowadays people prefer to search for comments and information on the internet than ask others opinions before they make purchases. However, there is massive information around the internet world. When people use the keywords to search in the comments, they will have to read a lot of texts and pages, which will take a bunch of time. This is not an easy job for people. The research "Subject analysis" and "Emotional analysis" help people to search for the diversity of emotional analysis consequences from movies. People won't have to review many comments to understand the movie evaluation. By collecting the half-year comments from PTT, this research has analyzed the adjective words to get the emotional score and use the score to build movie recommendations. After that, analyze the topics to get the topic models including the emotional score from analyzed words to give people the movie they prefer.