<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tsagkalidou, Katerina</style></author><author><style face="normal" font="default" size="100%">Vassiliki A. Koutsonikola</style></author><author><style face="normal" font="default" size="100%">Athena Vakali</style></author><author><style face="normal" font="default" size="100%">Konstantinos Kafetsios</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">D’Mello, Sidney K.</style></author><author><style face="normal" font="default" size="100%">Graesser, Arthur C.</style></author><author><style face="normal" font="default" size="100%">Schuller, Björn</style></author><author><style face="normal" font="default" size="100%">Martin, Jean-Claude</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Emotional Aware Clustering on Micro-blogging Sources</style></title><secondary-title><style face="normal" font="default" size="100%">ACII (1)</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Microblogging services</style></keyword><keyword><style  face="normal" font="default" size="100%">Sentiment analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">web clustering</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><volume><style face="normal" font="default" size="100%">6974</style></volume><pages><style face="normal" font="default" size="100%">387-396</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-24599-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Microblogging services have nowadays become a very popularcommunication tool among Internet users. Since millions of usersshare opinions on different aspects of life everyday, microblogging websites 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 onthe 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.&lt;/p&gt;
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