Mining the user clusters on Facebook fan pages based on topic and sentiment analysis

Kuan Cheng Lin, Shih Hung Wu, Liang Pu Chen, Tsun Ku, Gwo Dong Chen

研究成果: 書貢獻/報告類型會議論文篇章同行評審

5 引文 斯高帕斯(Scopus)

摘要

Social network websites such as Facebook, Tweeter, and Plurk have become a useful marketing toolkit. Many companies find that it can provide new opportunities on mining customers' opinions and get better understanding of the customers. The aim of the paper is to analyze the sentiment of users' opinions from corporation-run social networks, the Facebook Fan Pages. The goal is to find the topics and the associated sentiment of the topics in a given Fan Page run by a single corporation. Sentiment analysis in previous works was often based on a sentiment dictionary; we follow the traditional approach with the help of some additional rules to improve the performance. Combining the result of topic extraction and sentiment analysis, we try to find the most interested events in the given Fan Page. The results can be used in advanced marketing for the corporation and to satisfy more users.

原文???core.languages.en_GB???
主出版物標題Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014
編輯Elisa Bertino, Bhavani Thuraisingham, Ling Liu, James Joshi
發行者Institute of Electrical and Electronics Engineers Inc.
頁面627-632
頁數6
ISBN(電子)9781479958801
DOIs
出版狀態已出版 - 27 2月 2014
事件15th IEEE International Conference on Information Reuse and Integration, IEEE IRI 2014 - San Francisco, United States
持續時間: 13 8月 201415 8月 2014

出版系列

名字Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014

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???event.eventtypes.event.conference???15th IEEE International Conference on Information Reuse and Integration, IEEE IRI 2014
國家/地區United States
城市San Francisco
期間13/08/1415/08/14

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