Predicting depression of social media user on different observation windows

Proceedings - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2015

Volumn 1, Issue , 2016, Pages 361-364

  Hu, Quan ^a   Li, Ang ^b   Heng, Fei ^c   Li, Jianpeng ^c   Zhu, Tingshao ^d  

^a HENAN UNIVERSITY   (China)

^b BEIJING FORESTRY UNIVERSITY   (China)

^c LANZHOU UNIVERSITY   (China)

^d INSTITUTE OF PSYCHOLOGY   (China)

Author keywords

Classification; Depression; Machine learning; Microblogging behavior; Prediction

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA HANDLING; FORECASTING; INTELLIGENT AGENTS; LEARNING SYSTEMS; REGRESSION ANALYSIS;

BEHAVIORAL FEATURES; DATA COLLECTION; DEPRESSION; MICRO-BLOGGING; OBSERVATION WINDOW; PREDICTION ACCURACY; REGRESSION MODEL; SOCIAL MEDIA USERS;

SOCIAL NETWORKING (ONLINE);

EID: 85021834189     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WI-IAT.2015.166     Document Type: Conference Paper

References (16)

1. H. Herrman, S. Saxena, and R. Moodie, "Promoting mental health: concepts, emerging evidence, practice: a report of the World Health Organization, Department of Mental Health and Substance Abuse in collaboration with the Victorian Health Promotion Foundation and the University of Melbourne," World Health Organization, 2005, pp. 288.
2. B. A. Kitchener, A. F. Jorm, and D. C. Kelly, "Mental Health First Aid Manual," ORYGEN Research Centre, University of Melbourne, 2002.
3. C. D. Mathers, and D. Loncar, "Projections of global mortality and burden of disease from 2002 to 2030," PLoS medicine, 3(11), e442.
4. Centers for Disease Control and prevention (CDC), "Behavioral Risk Factor Surveillance System Survey Data," Atlanta, Georgia: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, 2008, 2011, 2012.
5. People's Daily, "The ghost of depression beside us," August 17, 2012.
6. Sina first quarter financial report, 2013.
7. Y. A. Hamburger, and E. Ben-Artzi, "The relationship between extraversion and neuroticism and the different uses of the Internet," Computers in Human Behavior, 16(4): 441-449, 2000.
8. K. J. Mitchell, C. Sabina, D. Finkelhor, and M. Wells, "Index of problematic online experiences: item characteristics and correlation with negative symptomatology," CyberPsychology & Behavior, 12(6): 707-711, 2009.
9. W. Peng, and M. Liu, "Online gaming dependency: a preliminary study in China," CyberPsychology, Behavior, and Social Networking, 13(3): 329-333, 2010.
10. F. Zhang, T. Zhu, A. Li, Y. Li, and X. Xu, "A survey of web behavior and mental health," In Pervasive Computing and Applications (ICPCA), 2011 6th International Conference on (pp. 189-195), IEEE.
11. L. Li, A. Li, B. Hao, Z. Guan, and T. Zhu, "Predicting Active Users' Personality Based on Micro-Blogging Behaviors," PloS one, 9(1), e84997, 2014.
12. L. S. Radloff, "The CES-D scale a self-report depression scale for research in the general population," Applied psychological measurement, 1(3): 385-401, 1977.
13. C. M. Bishop, "Pattern recognition and machine learning," New York: springer, p:205, 2006.
14. W. Guan, H. Gao, and M. Yang, et al, "Analyzing user behavior of the micro-blogging website Sina Weibo during hot social events," Physica A: Statistical Mechanics and its Applications, 395: 340-351, 2014.
15. P. A. Thoits, "Self, identity, stress, and mental health," Handbook of the sociology of mental health. Springer Netherlands, pp: 357-377, 2013.
16. C. Zhiyan, Y. Xiaodong, and L. Xinying, "Psychometric Features of CES-D in Chinese Adolescents," Chinese Journal of Clinical Psychology, Vol 17 (4), 443-448, 2009.