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Conscientiousness Measurement fromWeibo’s Public Information
Dong Nie; Lin L; Tingshao Zhu
2013
Source Publication不详
Correspondent Emailtszhu@psych.ac.cn.
Issue不详Pages:1-10
Other Abstract

We apply a graph-based semi-supervised learning algorithm to identify the conscientiousness of Weibo users. Given a set of Weibo users’ public information(e.g., number of followers) and a few labeled Weibo users, the task is to predict conscientiousness assessment for numeric unlabeled Weibo users. Singular value decomposition(SVD) technique is taken for feature reduction, and K nearest neighbor(KNN) method is used to recover a sparse graph. The local and global consistency algorithm is followed to deal with our data. Experiments demonstrate the advantage of semi-supervised learning over standard supervised learning when limited labeled data are available.

KeywordGraph-based Semi-supervised Learning Conscientiousness Identification Knn Svd
Indexed By其他
Language英语
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/25611
Collection社会与工程心理学研究室
Corresponding AuthorTingshao Zhu
AffiliationInstitute of Psychology, University of Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Dong Nie,Lin L,Tingshao Zhu. Conscientiousness Measurement fromWeibo’s Public Information[J]. 不详,2013(不详):1-10.
APA Dong Nie,Lin L,&Tingshao Zhu.(2013).Conscientiousness Measurement fromWeibo’s Public Information.不详(不详),1-10.
MLA Dong Nie,et al."Conscientiousness Measurement fromWeibo’s Public Information".不详 .不详(2013):1-10.
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