NDLI: Social Sentiment Detection of Event via Microblog

Content Provider	IEEE Xplore Digital Library
Author	Xinzhi Wang Xiangfeng Luo Jinjun Chen
Copyright Year	2013
Description	Author affiliation: Sch. of Comput. Eng. & Sci., Shanghai Univ., Shanghai, China (Xinzhi Wang; Xiangfeng Luo) \|\| Fac. of Eng. & Inf. Technol., Univ. of Technol. Sydney, Sydney, NSW, Australia (Jinjun Chen)
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.
Starting Page	1051
Ending Page	1058
File Size	594679
Page Count	8
File Format	PDF
ISBN	9780769550961
DOI	10.1109/CSE.2013.153
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-03
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computational modeling Training data sentiments analysis Aerospace electronics general sentiment model Controllability Educational institutions Vectors Stability analysis social sentiment detection
Content Type	Text
Resource Type	Article

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