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View all- Chen JTang X(undefined)The Challenges and Feasibility of Societal Risk Classification Based on Deep Learning of Representations2015 IEEE International Conference on Systems, Man, and Cybernetics10.1109/SMC.2015.110(569-574)
Exploring Societal Risk Classification of the Posts of Tianya Club
Authors: 
Jindong Chen, Xijin TangAuthors Info & Claims
Jindong Chen, Xijin TangAuthors Info & ClaimsPages 36 - 48
Abstract
To identify the societal risk category of the posts of Tianya Club, several studies are carried out toward the posts of Tianya Club. With 2-month manually risk labeled new posts published during December of 2011 to January of 2012, statistical analysis of posts is conducted at first. Later, similarity analysis of posts from one risk category, different risk categories and published on different days are implemented. Finally, multi-class classification of posts using support vector machine (SVM) with different training set is tested. The statistical analysis and similarity analysis reveals the difficulties in multi-class classification of the posts of Tianya Club. The multi-class predictive results indicate that SVM could be applied to multi-class classification of posts, but still need further exploitation.
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- Exploring Societal Risk Classification of the Posts of Tianya Club
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Published: 01 January 2014
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View all- Chen JTang X(undefined)The Challenges and Feasibility of Societal Risk Classification Based on Deep Learning of Representations2015 IEEE International Conference on Systems, Man, and Cybernetics10.1109/SMC.2015.110(569-574)