DocumentCode :
1688208
Title :
Sentiment diffusion in large scale social networks
Author :
Jie Tang ; Fong, A.C.M.
Author_Institution :
Tsinghua Univ., Beijing, China
fYear :
2013
Firstpage :
244
Lastpage :
245
Abstract :
Popularity of online social networks provides the chance to make sentiment analysis on every user instead of every document or sentence. And relations between users on social media sites often indicate correlation (negation) between users´ opinions. In this work, we study how user´s opinion spread in social networks. We employ the data from Tencent.com, the largest social network of China to empirically study the problem. Our work focuses on six different topics including policy, products, brand, sports, movie and politician. We study the distributions of peoples´ opinions on different topics and how users´ opinions are influenced by those he is following. We propose a graphical model to capture the essence of social network as well as an algorithm to perform semi-supervised learning. The learning algorithm can be used to accurately predict users´ sentiment in the social network.
Keywords :
learning (artificial intelligence); social networking (online); graphical model; large scale social networks; online social networks; semisupervised learning algorithm; sentiment analysis; sentiment diffusion; social media sites; Context; Data models; Prediction algorithms; Predictive models; Semisupervised learning; Sentiment analysis; Social network services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Consumer Electronics (ICCE), 2013 IEEE International Conference on
Conference_Location :
Las Vegas, NV
ISSN :
2158-3994
Print_ISBN :
978-1-4673-1361-2
Type :
conf
DOI :
10.1109/ICCE.2013.6486878
Filename :
6486878
Link To Document :
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