Mining the interests of Chinese microbloggers via keyword extraction

作者: Xinxiong Chen , Maosong Sun , Zhiyuan Liu

DOI: 10.1007/S11704-011-1174-8

关键词:

摘要: Microblogging provides a new platform for communicating and sharing information among Web users. Users can express opinions record daily life using microblogs. Microblogs that are posted by users indicate their interests to some extent. We aim mine user via keyword extraction from Traditional methods usually designed formal documents such as news articles or scientific papers. Messages microblogging users, however, noisy full of words, which is challenge extraction. In this paper, we combine translation-based method with frequency-based our experiments, extract keywords microblog the largest website in China, Sina Weibo. The results show identify users' accurately efficiently.

参考文章(63)
Jianguo Xiao, Xiaojun Wan, Single document keyphrase extraction using neighborhood knowledge national conference on artificial intelligence. pp. 855- 860 ,(2008)
Patrick Paroubek, Alexander Pak, Twitter as a Corpus for Sentiment Analysis and Opinion Mining language resources and evaluation. ,(2010)
Xinxiong Chen, Maosong Sun, Zhiyuan Liu, Yabin Zheng, Automatic Keyphrase Extraction by Bridging Vocabulary Gap conference on computational natural language learning. pp. 135- 144 ,(2011)
William B. Dolan, Chris Brockett, Chris Quirk, Monolingual Machine Translation for Paraphrase Generation empirical methods in natural language processing. pp. 142- 149 ,(2004)
Aron Culotta, Detecting influenza outbreaks by analyzing Twitter messages arXiv: Information Retrieval. ,(2010)
Rada Mihalcea, Paul Tarau, TextRank: Bringing Order into Text empirical methods in natural language processing. pp. 404- 411 ,(2004)
Andranik Tumasjan, Isabell M. Welpe, Philipp G. Sandner, Timm Oliver Sprenger, Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment international conference on weblogs and social media. ,(2010)