A unified approach for domain-specific tweet sentiment analysis

Patricia L.V. Ribeiro, Li Weigang, Tiancheng Li

科研成果: 书/报告/会议事项章节会议稿件同行评审

5 引用 (Scopus)

摘要

Twitter is an online social networking (OSN) service that enables users to send and read short messages called 'tweets'. As of December 2014, Twitter has more than 500 million users, out of which more than 284 million are active users and about 500 million tweets are posted every day. Tweet sentiment analysis (TSA) identifies a valuable platform for the OSN study which provides insights into the opinion of the public about culture, products and political agendas and thereby is able to predict the trends in specific domains. In order to execute efficient TSA on a particular topic or domain, a TSA approach with unified tool, UnB TSA, is proposed consisting of four steps: tweets collection, refinement (excluding noisy tweets), sentiment lexicon creation and sentiment analysis. As a key part, the lexicon is domain-specific that incorporates expressions whose sentiment varies from one domain to another. Four algorithms including expanding limited hashtags into a larger and more complete set to collect tweets have been implemented. Experiments on the 'iPhone 6' domain which obtains convincing results in all of the four phases, showing the superiority of the domain-specific TSA approach over a generic one.

源语言英语
主期刊名2015 18th International Conference on Information Fusion, Fusion 2015
出版商Institute of Electrical and Electronics Engineers Inc.
846-853
页数8
ISBN(电子版)9780982443866
出版状态已出版 - 14 9月 2015
已对外发布
活动18th International Conference on Information Fusion, Fusion 2015 - Washington, 美国
期限: 6 7月 20159 7月 2015

出版系列

姓名2015 18th International Conference on Information Fusion, Fusion 2015

会议

会议18th International Conference on Information Fusion, Fusion 2015
国家/地区美国
Washington
时期6/07/159/07/15

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