The aim of this research is to easily monitor the reputation of a company in the Twittersphere. We propose a strategy that organizes a stream of tweets into different clusters based on the tweets' topics. Furthermore, the obtained clusters are assigned into different priority levels. A cluster with high priority represents a topic which may affect the reputation of a company, and that consequently deserves immediate attention. The evaluation results show that our method is competitive even though the method does not make use of any external knowledge resource. © 2013 Springer-Verlag.
Qureshi, M., O'Riordan, C., Pasi, G. (2013). Clustering with error-estimation for monitoring reputation of companies on Twitter. In 9th Asia Information Retrieval Societies Conference on Information Retrieval Technology, AIRS 2013; Singapore; Singapore; 9-11 December 2013 (pp.170-180) [10.1007/978-3-642-45068-6_15].
Clustering with error-estimation for monitoring reputation of companies on Twitter
QURESHI, MUHAMMAD ATIF;PASI, GABRIELLA
2013
Abstract
The aim of this research is to easily monitor the reputation of a company in the Twittersphere. We propose a strategy that organizes a stream of tweets into different clusters based on the tweets' topics. Furthermore, the obtained clusters are assigned into different priority levels. A cluster with high priority represents a topic which may affect the reputation of a company, and that consequently deserves immediate attention. The evaluation results show that our method is competitive even though the method does not make use of any external knowledge resource. © 2013 Springer-Verlag.
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