Using Text Mining to Extract Issues for School: an Empirical Study of the Social Platform-Dcard

• Main Authors: Shu-Fen Chiou, Hsin-Yi Wang, Jung-Wen Lo
• Format: Article
• Language: English
• Published: Taiwan Association of Engineering and Technology Innovation 2017-12-01
• Series: Proceedings of Engineering and Technology Innovation
• Subjects: text mining; big data; social platform; sentiment
• Online Access: http://ojs.imeti.org/index.php/PETI/article/view/995

Nowadays, social network within sentiment analysis has become the main trend in text mining domain. There are many platforms have been analyzed, such as Facebook, Twitter, Instagram, and so on. In our manuscript, we attempt to extract the information about the sentiment polarity of messages (positive, neutral or negative) in a social platform “Dcard”. The users of Dcard are Taiwanese college students, and anonymous post is being used this in social platform, therefore, the user can express their opinion more freedom. We use Dcard to the sentiment polarity of messages in extract the information about the school; moreover, the school could get the feedback from this finding to improve their policy. In this paper, we used python to scrap the web page, and the sentiment lexicon would be built.