DocumentCode :
2853048
Title :
Towards detecting emotional communities in Twitter
Author :
Kanavos, Andreas ; Perikos, Isidoros
Author_Institution :
Comput. Eng. & Inf. Dept., Univ. of Patras, Patras, Greece
fYear :
2015
fDate :
13-15 May 2015
Firstpage :
524
Lastpage :
525
Abstract :
The analysis of social networks is a very challenging research area while a fundamental aspect concerns the detection of user communities. In this paper we present a novel methodology for community detection based on users´ emotional behavior. The methodology analyzes user´s tweets in order to determine their emotional behavior in Ekman emotional scale. We define one metric so as to count the influence of produced communities. Our results are quite promising in terms of creating influential enough communities.
Keywords :
emotion recognition; social networking (online); Ekman emotional scale; Twitter; emotional community detection; social network analysis; user community detection; user emotional behavior; user tweet analysis; Adaptation models; Communities; Emotion recognition; Measurement; Sentiment analysis; Twitter; Influential Community Detection; Tweet Emotion Recognition; User Influence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Research Challenges in Information Science (RCIS), 2015 IEEE 9th International Conference on
Conference_Location :
Athens
Type :
conf
DOI :
10.1109/RCIS.2015.7128919
Filename :
7128919
Link To Document :
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