Mining on Public Sentiment Based on Net Loan Comments


Authors : Daohai Zhang, Gui Ren, Youcai Yang, Barry Bishop, Hiroshi Honda.

Volume/Issue : Volume 3 - 2018, Issue 8 - August

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://goo.gl/phTm9a

Thomson Reuters ResearcherID : https://goo.gl/3bkzwv

With the growing dependency of network socialization, the information released by users has gradually become a valuable data source for enterprise competition and intelligence analysis. Recently, net loans have been developing rapidly, but several have gradually become a unique phenomenon in China. This research focuses on the comment label of net loans using the sentiment analysis and topic LDA mining method. It begins with data pre-processing, classification of comment label topic mining, and grasping the overall concern of users on the net loan platform. It then examines making the comment label for sentiment classification. Finally, the comments are mined again and analyzed by emotional theme distribution under different emotional words. The research results show that positive sentiment of the net loan platform includes investment cycle, the history of the anticipated annualized rate, payment methods of return, service fees, simultaneous capital security, income security, user experience, and platform supervision.

Keywords : Sentiment analysis, net loan, text mining, LDA mining method, platform.

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