@inproceedings{bb1a62426abb4153aee6a3c833089ec2,
title = "Hashtag sense induction based on co-occurrence graphs",
abstract = "Twitter hashtags are used to categorize tweets for improving search categorizing topic. But the fact that people can create and use hashtags freely leads to a situation such that one hashtag may have multiple senses. In this paper, we propose a method to induce senses of a hashtag in a particular time frame. Our assumption is that for a sense of a hashtag the context words around it are similar. Then we design a method that uses a co-occurrence graph and community detection algorithm. Both words and hashtags are nodes of the cooccurrence graph, and an edge represents the relation of two nodes co-occurring in the same tweet. A list of words with a high node degree representing a sense is extracted as a community of the graph. We take Wikipedia disambiguation list page as word sense inventory to refine the results by removing non-sense topics.",
keywords = "Co-occurrence Graph, Hashtag, Sense induction, Twitter, Wikipedia",
author = "Mengmeng Wang and Mizuho Iwaihara",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 17th Asia-PacificWeb Conference, APWeb 2015 ; Conference date: 18-09-2015 Through 20-09-2015",
year = "2015",
doi = "10.1007/978-3-319-25255-1_13",
language = "English",
isbn = "9783319252544",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "154--165",
editor = "Reynold Cheng and Bin Cui and Zhenjie Zhang and Ruichu Cai and Jia Xu",
booktitle = "Web Technologies and Applications - 17th Asia-PacificWeb Conference,APWeb 2015, Proceedings",
}