Predicting personality with social media

ABSTRACT

Social media is a place where users present themselves to the world, revealing personal details and insights into their lives. We are beginning to understand how some of this information can be utilized to improve the users' experiences with interfaces and with one another. In this paper, we are interested in the personality of users. Personality has been shown to be relevant to many types of interactions; it has been shown to be useful in predicting job satisfaction, professional and romantic relationship success, and even preference for different interfaces. Until now, to accurately gauge users' personalities, they needed to take a personality test. This made it impractical to use personality analysis in many social media domains. In this paper, we present a method by which a user's personality can be accurately predicted through the publicly available information on their Facebook profile. We will describe the type of data collected, our methods of analysis, and the results of predicting personality traits through machine learning. We then discuss the implications this has for social media design, interface design, and broader domains.

References

1. A. Acar and M. Polonsky. Online Social Networks and Insights into Marketing Communications. Journal of Internet Commerce, 6(4):55--72, 2008.
2. M. Back, J. Stopfer, S. Vazire, S. Gaddis, S. Schmukle, B. Egloff, and S. Gosling. Facebook Profiles Reflect Actual Personality, Not Self-Idealization. Psychological Science, 21(3):372, 2010.
3. W.-P. Brinkman and N. Fine. Towards customized emotional design: an explorative study of user personality and user interface skin preferences. In EACE '05: Proceedings of the 2005 annual conference on European association of cognitive ergonomics, pages 107--114. University of Athens, 2005.
4. P. Costa Jr, A. Terracciano, and R. McCrae. Gender differences in personality traits across cultures: Robust and surprising findings. Journal of Personality and Social Psychology, 81(2):322--331, 2001.
5. S. Dollinger. Research Note: Personality and Music Preference: Extraversion and Excitement Seeking or Openness to Experience? Psychology of Music, 21(1):73, 1993.
6. E. Gilbert and K. Karahalios. Predicting tie strength with social media. In Proceedings of the 27th international conference on Human factors in computing systems, pages 211--220. ACM New York, NY, USA, 2009.
7. J. Golbeck. Computing and Applying Trust in Web-based Social Networks. PhD thesis, University of Maryland, College Park, MD, USA, April 2005.
8. M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. Witten. The WEKA data mining software: An update. ACM SIGKDD Explorations Newsletter, 11(1):10--18, 2009.
9. C. Hansen and R. Hansen. Constructing personality and social reality through music: Individual differences among fans of punk and heavy metal music. Journal of broadcasting & electronic media, 35(3):335--350, 1991.
10. G. Holmes, M. Hall, and E. Prank. Generating rule sets from model trees. Advanced Topics in Artificial Intelligence, pages 1--12, 1999.
11. O. D. John. Big five inventory, 2000.
12. A. Karsvall. Personality preferences in graphical interface design. In NordiCHI '02: Proceedings of the second Nordic conference on Human-computer interaction, pages 217--218, New York, NY, USA, 2002. ACM.
13. F. Mairesse, M. Walker, M. Mehl, and R. Moore. Using linguistic cues for the automatic recognition of personality in conversation and text. Journal of Artificial Intelligence Research, 30(1):457--500, 2007.
14. C. Nass and K. M. Lee. Does computer-generated speech manifest personality? an experimental test of similarity-attraction. In CHI '00: Proceedings of the SIGCHI conference on Human factors in computing systems, pages 329--336, New York, NY, USA, 2000. ACM.
15. G. Odekerken-Schroder, K. De Wulf, and P. Schumacher. Strengthening outcomes of retailer-consumer relationships:: The dual impact of relationship marketing tactics and consumer personality. Journal of Business Research, 56(3):177--190, 2003.
16. J. Pennebaker, M. Francis, and R. Booth. Linguistic inquiry and word count: LIWC 2001. Mahway: Lawrence Erlbaum Associates, 2001.
17. J. Pennebaker and L. King. Linguistic styles: Language use as an individual difference. Journal of personality and social psychology, 77(6):1296--1312, 1999.
18. J. Quinlan. Learning with continuous classes. In 5th Australian joint conference on artificial intelligence, pages 343--348. Citeseer, 1992.
19. D. Rawlings and V. Ciancarelli. Music preference and the five-factor model of the NEO Personality Inventory. Psychology of Music, 25(2):120, 1997.
20. P. Rentfrow and S. Gosling. The do re mi's of everyday life: The structure and personality correlates of music preferences. Journal of Personality and Social Psychology, 84(6):1236--1256, 2003.
21. P. Rosen and D. Kluemper. The Impact of the Big Five Personality Traits on the Acceptance of Social Networking Website. AMCIS 2008 Proceedings, page 274, 2008.
22. J. Schrammel, C. Köffel, and M. Tscheligi. Personality traits, usage patterns and information disclosure in online communities. In BCS HCI '09: Proceedings of the 2009 British Computer Society Conference on Human-Computer Interaction, pages 169--174, Swinton, UK, UK, 2009. British Computer Society.
23. M. Selfhout, W. Burk, S. Branje, J. Denissen, M. van Aken, and W. Meeus. Emerging Late Adolescent Friendship Networks and Big Five Personality Traits: A Social Network Approach. Journal of personality, 78(2):509--538, 2010.

Index Terms

• Human-centered computing

  • Collaborative and social computing