thedistributedrepresentationforsocietalriskclassificationtowardbbsposts

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	thedistributedrepresentationforsocietalriskclassificationtowardbbsposts
	Chen Jindong; Tang Xijin
	2017
发表期刊	journalofsystemssciencecomplexity
ISSN	1009-6124
卷号	30 期号:3 页码:627
摘要	The risk classification of BBS posts is important to the evaluation of societal risk level within a period. Using the posts collected from Tianya forum as the data source, the authors adopted the societal risk indicators from socio psychology, and conduct document-level multiple societal risk classification of BBS posts. To effectively capture the semantics and word order of documents, a shallow neural network as Paragraph Vector is applied to realize the distributed vector representations of the posts in the vector space. Based on the document vectors, the authors apply one classification method KNN to identify the societal risk category of the posts. The experimental results reveal that paragraph vector in document-level societal risk classification achieves much faster training speed and at least 10% improvements of F-measures than Bag-of-Words. Furthermore, the performance of paragraph vector is also superior to edit distance and Lucene-based search method. The present work is the first attempt of combining document embedding method with socio psychology research results to public opinions area.
语种	英语
资助项目	[National Natural Science Foundation of China]
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/45865
专题	系统科学研究所
作者单位	中国科学院数学与系统科学研究院
推荐引用方式 GB/T 7714	Chen Jindong,Tang Xijin. thedistributedrepresentationforsocietalriskclassificationtowardbbsposts[J]. journalofsystemssciencecomplexity,2017,30(3):627.
APA	Chen Jindong,&Tang Xijin.(2017).thedistributedrepresentationforsocietalriskclassificationtowardbbsposts.journalofsystemssciencecomplexity,30(3),627.
MLA	Chen Jindong,et al."thedistributedrepresentationforsocietalriskclassificationtowardbbsposts".journalofsystemssciencecomplexity 30.3(2017):627.