DocumentCode :
637087
Title :
Multi-objects sentiment vector aggregation: An approach to extract latent cyber organizations
Author :
Wenli Liu ; Hao Lu ; Min Zheng ; Julei Fu ; Tao Wang
Author_Institution :
Center of Mil. Comput. Experiments & Parallel, Nat. Univ. of Defense, Changsha, China
fYear :
2013
fDate :
28-30 July 2013
Firstpage :
302
Lastpage :
306
Abstract :
This paper aims at discovering latent cyber organizations in rich social media, through analysis sentiment dimension of individual´s social attribute. From a sociology perspective, people who have the same point of views will have great probabilities and opportunities to aggression together. Monitoring these latent cyber organizations can help us understanding the tendency of social events. Naturally, individual will have his own opinions towards different objects, such as persons, events, organizations, or topics etc. We propose an effective framework to compute the individual´s opinion towards certain multiple objects as his sentiment vector. Then, we detected latent cyber organizations based on the individuals´ sentiment vector. To validate our approach, we illustrate the usefulness of our framework through an experiment in Sina microblog dataset, and the results demonstrate to be valuable.
Keywords :
organisational aspects; probability; social networking (online); social sciences computing; Sina microblog dataset; latent cyber organizations; multiobjects sentiment vector aggregation; probabilities; social media; sociology perspective; Clustering algorithms; Communities; Cyberspace; Educational institutions; Organizations; Sociology; Vectors; community extraction; latent cyber organization; sentiment computing; sentiment vetor; social computing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Service Operations and Logistics, and Informatics (SOLI), 2013 IEEE International Conference on
Conference_Location :
Dongguan
Print_ISBN :
978-1-4799-0529-4
Type :
conf
DOI :
10.1109/SOLI.2013.6611430
Filename :
6611430
Link To Document :
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