Abstract
In recent years, the number of social networks users has shown explosive growth. In this context, social media provides researchers with plenty of information about user behavior and social behavior. We are beginning to understand user’s behavior on social media is related to user’s personality. Conventional personality assessment depends on self-report inventory, which costs a lot to collect information. This paper tries to predict user’s Big-Five personality through their information on social networks. We conducted a Big-Five personality inventory test with 131 users of Chinese social network Sina Weibo, and crawled all of their Weibo texts and profile information. By studying the relevance between all types of user generated information and personality results of users, we extracted five most relative dimensionalities and used machine learning method to successfully predict the Big-Five personality of users.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Goldberg, L.: The structure of phenotypic personality traits. American Psychologist 48(1), 26 (1993)
Back, M., Stopfer, J., Vazire, S., Gaddis, S., Schmukle, S., Egloff, B., Gosling, S.: Facebook Profiles Reflect Actual Personality, Not Self-Idealization. Psychological Science 21(3), 372 (2010)
Burger, J.: Personality. Thomson Wadsworth, Belmont (2008)
Li, L., Li, A., Hao, B., Guan, Z., Zhu, T.: Predicting Active Users’ Personality Based on Micro-Blogging Behaviors. PLoS ONE 9(1), e84997 (2014), doi:10.1371/journal.pone.0084997
Golbeck, J., Robles, C., Edmondson, M., Turner, K.: Predicting personality from Twitter. In: Proceedings of 2011 IEEE Third International Conference on Privacy, Security, Risk and Trust (Passat) and 2011 IEEE Third International Conference on Social Computing (Socialcom) (2011)
Golbeck, J., Robles, C., Turner, K.: Predicting personality with social meida. In: Proceedings of CHI 2011 Extended Abstracts on Human Factors in Computing Systems (2011)
Quercia, D., Kosinski, M., Stillwell, D., Crowcroft, J.: Our Twitter profiles, our selves: Predicting personality with Twitter. In: Proceedings of 2011 IEEE Third International Conference on Privacy, Security, Risk and Trust (Passat) and 2011 IEEE Third International Conference on Social Computing (Socialcom) (2011)
Bai, S., Hao, B., Li, A., et al.: Predicting Big Five Personality Traits of Microblog Users. In: 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), vol. 1, pp. 501–508. IEEE (2013)
Rapoza, K.: China’s Weibos vs US’s Twitter: And the Winner Is? Forbes (May 17, 2011) (retrieved August 4, 2011)
Gosling, S.D., Augustine, A.A., Vazire, S.: Manifestations of personality in online social networks: Self-reported facebook-related behaviors and observable profile information. Cyberpsy-chology, Behavior, and Social Networking 14(9), 483–488 (2011)
Costa Jr., P.T., McCrae, R.R.: Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI) manual. Psychological Assessment Resources, Odessa (1992)
Tupes, E., Christal, R.: Recurrent personality factors based on trait ratings. Journal of Personality 60(2), 225–251 (1992)
McCrae, R., John, O.: An introduction to the five-factor model and its applications. Journal of Personality 60(2), 175–215 (1992)
Digman, J.: Personality structure: Emergence of the five-factor model. Annual Review of Psychology 41(1), 417–440 (1990)
John, O.: The Big Five factor taxonomy: Dimensions of personality in the natural language and in questionnaires. In: Handbook of Personality: Theory and Research, vol. 14, pp. 66–100 (1990)
McCrae, R.: Why I advocate the five-factor model: Joint factor analyses of the NEO-PI with other instruments. In: Personality Psychology: Recent Trends and Emerging Directions, pp. 237–245 (1989)
Schmitt, D., Allik, J., McCrae, R., Benet-Martinez, V.: The geographic distribution of Big Five personality traits: Patterns and profiles of human self-description across 56 nations. Journal of Cross-Cultural Psychology 38(2), 173 (2007)
Schrammel, J., Köffel, C., Tscheligi, M.: Personality traits, usage patterns and information disclosure in online communities. In: BCS HCI 2009: Proceedings of the 2009 British Computer Society Conference on Human-Computer Interaction, pp. 169–174. British Computer Society, Swinton (2009)
Pennebaker, J., Francis, M., Booth, R.: Linguistic inquiry and word count: LIWC 2001. Lawrence Erlbaum Associates, Mahway (2001)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.: The WEKA data mining software: An update. ACM SIGKDD Explorations Newsletter 11(1), 10–18 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wan, D., Zhang, C., Wu, M., An, Z. (2014). Personality Prediction Based on All Characters of User Social Media Information. In: Huang, H., Liu, T., Zhang, HP., Tang, J. (eds) Social Media Processing. SMP 2014. Communications in Computer and Information Science, vol 489. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45558-6_20
Download citation
DOI: https://doi.org/10.1007/978-3-662-45558-6_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45557-9
Online ISBN: 978-3-662-45558-6
eBook Packages: Computer ScienceComputer Science (R0)