Social sentiment detection of event via microblog

Wang, X; Luo, X; Chen, J

Social sentiment detection of event via microblog

Wang, X Luo, X Chen, J

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013, 2013, pp. 1051 - 1058
Issue Date:: 2013-12-01

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Field	Value	Language
dc.contributor.author	Wang, X	en_US
dc.contributor.author	Luo, X	en_US
dc.contributor.author	Chen, J	en_US
dc.date.issued	2013-12-01	en_US
dc.identifier.citation	Proceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013, 2013, pp. 1051 - 1058	en_US
dc.identifier.uri	http://hdl.handle.net/10453/28371
dc.description.abstract	Sentimental analyses of the public have been attracting increasing attentions from researchers. This paper focuses on the research problem of social sentiment detection, which aims to identify the sentiments of the public evoked by online microblogs. A general social sentiment model is proposed for this task. The general social sentiment model combining society and phycology knowledge are employed to measure social sentiment state. Then, we detail computation of sentiment vector to extract sentiment distribution of blogger on event. Besides, social state for events are computed based on the general social sentiment model and sentiment vectors. Furthermore, we certify that social sentiment are not independent but are correlated with each other heterogeneously in different events. The dependencies between sentiments can provide guidance in decision-making for government or organization. At last experiments on two real-world collections of events microblogs are conducted to prove the performance of our method. © 2013 IEEE.	en_US
dc.relation.ispartof	Proceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013	en_US
dc.relation.isbasedon	10.1109/CSE.2013.153	en_US
dc.title	Social sentiment detection of event via microblog	en_US
dc.type	Conference Proceeding
utslib.for	0899 Other Information and Computing Sciences	en_US
dc.location.activity	Sydney, Australia	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Sentimental analyses of the public have been attracting increasing attentions from researchers. This paper focuses on the research problem of social sentiment detection, which aims to identify the sentiments of the public evoked by online microblogs. A general social sentiment model is proposed for this task. The general social sentiment model combining society and phycology knowledge are employed to measure social sentiment state. Then, we detail computation of sentiment vector to extract sentiment distribution of blogger on event. Besides, social state for events are computed based on the general social sentiment model and sentiment vectors. Furthermore, we certify that social sentiment are not independent but are correlated with each other heterogeneously in different events. The dependencies between sentiments can provide guidance in decision-making for government or organization. At last experiments on two real-world collections of events microblogs are conducted to prove the performance of our method. © 2013 IEEE.

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http://hdl.handle.net/10453/28371