Sentiment-based influence detection on Twitter

The user generated content available in online communities is easy to create and consume. Lately, it also became strategically important to companies interested in obtaining population feedback on products, merchandising, etc. One of the most important online communities is Twitter: recent statistic...

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Bibliographic Details
Published inJournal of the Brazilian Computer Society Vol. 18; no. 3; pp. 169 - 183
Main Authors Bigonha, Carolina, Cardoso, Thiago N. C., Moro, Mirella M., Gonçalves, Marcos A., Almeida, Virgílio A. F.
Format Journal Article
LanguageEnglish
Published London Springer London 01.09.2012
Sociedade Brasileira de Computação
Subjects
Computer Science
Computer System Implementation
Data Structures
Operating Systems
Simulation and Modeling
Webmedia 2010
User influence
Twitter
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Summary:The user generated content available in online communities is easy to create and consume. Lately, it also became strategically important to companies interested in obtaining population feedback on products, merchandising, etc. One of the most important online communities is Twitter: recent statistics report 65 million new tweets each day. However, processing this amount of data is very costly and a big portion of the content is simply not useful for strategic analysis. Thus, in order to filter the data to be analyzed, we propose a new method for ranking the most influential users in Twitter. Our approach is based on a combination of the user position in networks that emerge from Twitter relations, the polarity of her opinions and the textual quality of her tweets. Our experimental evaluation shows that our approach can successfully identify some of the most influential users and that interactions between users provide the best evidence to determine user influence.
ISSN:0104-6500
1678-4804
DOI:10.1007/s13173-011-0051-5