Personality Prediction for Microblog Users with Active Learning Method

被引：1
|
作者：
Liu, Xiaoqian [1 ]
Nie, Dong [2 ]
Bai, Shuotian [2 ]
Hao, Bibo [2 ]
Zhu, Tingshao [1 ]
机构：
[1] Chinese Acad Sci, Inst Psychol, Beijing 100101, Peoples R China
[2] Univ Chinese Acad Sci, Beijing, Peoples R China
来源：
HUMAN CENTERED COMPUTING, HCC 2014 | 2015年 / 8944卷
关键词：
Active learning; Personality; Online behavior; REGRESSION;
D O I：
10.1007/978-3-319-15554-8_4
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Personality research on social media is a hot topic recently due to the rapid development of social medias well as the central importance of personality in psychology, but it is hard to acquire adequate appropriate labeled samples. Our research aims to choose the right users to be labeled to improve the accuracy of predicting. a few labeled users, the task is to predict personality of other unlabeled users Given a set of Microblog users' public information (e.g., number of followers) and. The active learning regression algorithm has been employed to establish predicting model in this paper, and the experimental results demonstrate our method can fairly well predict the personality of Microblog users.
引用
收藏
页码：41 / 54
页数：14
相关论文
共 50 条
  • [1] Predicting Big Five Personality Traits of Microblog Users
    Bai, Shuotian
    Hao, Bibo
    Li, Ang
    Yuan, Sha
    Gao, Rui
    Zhu, Tingshao
    2013 IEEE/WIC/ACM INTERNATIONAL JOINT CONFERENCES ON WEB INTELLIGENCE (WI) AND INTELLIGENT AGENT TECHNOLOGIES (IAT), VOL 1, 2013, : 501 - 508
  • [2] Active Learning for Entity Filtering in Microblog Streams
    Spina, Damiano
    Peetz, Maria-Hendrike
    de Rijke, Maarten
    SIGIR 2015: PROCEEDINGS OF THE 38TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, 2015, : 975 - 978
  • [3] Personality Prediction of Social Network Users
    Li, Chaowei
    Wan, Jiale
    Wang, Bo
    2017 16TH INTERNATIONAL SYMPOSIUM ON DISTRIBUTED COMPUTING AND APPLICATIONS TO BUSINESS, ENGINEERING AND SCIENCE (DCABES), 2017, : 84 - 87
  • [4] A Transfer Learning Approach for Emotion Intensity Prediction in Microblog Text
    Osama, Mohamed
    El-Beltagy, Samhaa R.
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT SYSTEMS AND INFORMATICS 2019, 2020, 1058 : 512 - 522
  • [5] Prediction of Personality Traits in Twitter Users with Latent Features
    Jaimes Moreno, Daniel Ricardo
    Gomez, Juan Carlos
    Almanza-Ojeda, Dora-Luz
    Ibarra-Manzano, Mario-Alberto
    2019 INTERNATIONAL CONFERENCE ON ELECTRONICS, COMMUNICATIONS AND COMPUTERS (CONIELECOMP), 2019, : 176 - 181
  • [6] Personality Prediction Based on Content of Facebook Users:A Literature Review
    Aung, Zan Mo Mo
    Myint, Phyu Hninn
    2019 20TH IEEE/ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING AND PARALLEL/DISTRIBUTED COMPUTING (SNPD), 2019, : 34 - 38
  • [7] Effects of Active Learning and Adaptive Behavior on Personality of Football Players in China
    Sun, Bole
    REVISTA DE PSICOLOGIA DEL DEPORTE, 2022, 31 (01): : 148 - 157
  • [8] Active Learning for microRNA Prediction
    Hassani, Mohsen Sheikh
    Green, James R.
    PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM), 2018, : 5 - 12
  • [9] Corpus Expansion for Neural CWS on Microblog-Oriented Data with λ-Active Learning Approach
    Zhang, Jing
    Huang, Degen
    Huang, Kaiyu
    Liu, Zhuang
    Ren, Fuji
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2018, E101D (03): : 778 - 785
  • [10] "Are we tweeting our real selves?" personality prediction of Indian Twitter users using deep learning ensemble model
    Mahajan, Rhea
    Mahajan, Remia
    Sharma, Eishita
    Mansotra, Vibhakar
    COMPUTERS IN HUMAN BEHAVIOR, 2022, 128
12345