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Predicting Personality On Social Media with Semi-supervised Learning
Nie, D (Nie, Dong)1; Guan, ZD (Guan, Zengda); Hao, BB (Hao, Bibo); Bai, ST (Bai, Shuotian); (Zhu, Tingshao)
第一作者Nie, D (Nie, Dong)
2014
会议名称IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (WI-IAT)
通讯作者邮箱tszhu@psych.ac.cn
会议录名称2014 IEEE/WIC/ACM INTERNATIONAL JOINT CONFERENCES ON WEB INTELLIGENCE (WI) AND INTELLIGENT AGENT TECHNOLOGIES (IAT), VOL 2
卷号2
期号不详
页码158-165
会议日期AUG 11-14, 2014
会议地点Univ Warsaw, Warsaw, POLAND
摘要

Personality research on social media is a hot topic recently due to the rapid development of social media as well as the central importance of personality study in psychology, but most studies are conducted on inadequate label samples. Our research aims to explore the usage of unlabeled samples to improve the prediction accuracy. By conducting n user study with 1792 users, we adopt local linear semi-supervised regression algorithm to predict the personality traits of Microblog users. Given a set of Microblog users' public information (e.g., number of followers) and a few labeled users, the task is to predict personality of other unlabeled users. The local linear semi-supervised regression algorithm has been employed to establish prediction model in this paper, and the experimental results demonstrate the usage of unlabeled data can improve the accuracy of prediction.

关键词Local Linear Kernel Regression Unlabeled Data Personality Prediction
DOI10.1109/WI-IAT.2014.93
语种英语
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被引频次:7[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符http://ir.psych.ac.cn/handle/311026/26557
专题社会与工程心理学研究室
作者单位1.Univ Chinese Acad Sci, Inst Psychol, Beijing, Peoples R China
2.Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式
GB/T 7714
Nie, D ,Guan, ZD ,Hao, BB ,et al. Predicting Personality On Social Media with Semi-supervised Learning[C],2014:158-165.
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