Abstract
Microblogging services have nowadays become a very popular communication tool among Internet users. Since millions of users share opinions on different aspects of life everyday, microblogging web-sites are considered as a credible source for exploring both factual and subjective information. This fact has inspired research in the area of automatic sentiment analysis. In this paper we propose an emotional aware clustering approach which performs sentiment analysis of users tweets on the basis of an emotional dictionary and groups tweets according to the degree they express a specific set of emotions. Experimental evaluations on datasets derived from Twitter prove the efficiency of the proposed approach.
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Tsagkalidou, K., Koutsonikola, V., Vakali, A., Kafetsios, K. (2011). Emotional Aware Clustering on Micro-blogging Sources. In: D’Mello, S., Graesser, A., Schuller, B., Martin, JC. (eds) Affective Computing and Intelligent Interaction. ACII 2011. Lecture Notes in Computer Science, vol 6974. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24600-5_42
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DOI: https://doi.org/10.1007/978-3-642-24600-5_42
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