Skip to main content
Log in

Predicting personality with social behavior: a comparative study

  • Original Article
  • Published:
Social Network Analysis and Mining Aims and scope Submit manuscript

Abstract

In this paper, we study the problem of predicting personality with features based on social behavior. While network position and text analysis are often used in personality prediction, the use of social behavior is fairly new. Often studies of social behavior either concentrate on a single behavior or trait, or simply use behavior to predict ties that are then used in analysis of network position. To study this problem, we introduce novel features based on a person’s social actions in general, towards specific individuals in particular. We also compute the variation of these actions among all the social contacts of a person as well as the actions of friends. We show that social behavior alone, without the help of any textual or network position information, provides a good basis for personality prediction. We then provide a unique comparative study that finds the most significant features based on social behavior in predicting personality for three different communication mediums: Twitter, SMS and phone calls. These mediums offer us with social behavior from public and private contexts, containing messaging and voice call type exchanges. We find behaviors that are distinctive and normative among the ones we study. We also illustrate how behavioral features relate to different personality traits. We also show the various similarities and differences between different mediums in terms of social behavior. Note that all behavioral features are based on statistical properties of the number and the time of social actions and do not consider the textual content. As a result, they can be applied in many different settings. Furthermore, our findings show us how behavioral features can be customized to a specific medium and personality trait.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Notes

  1. http://trec.nist.gov/data/tweets/.

References

  • Adalı S, Escriva R, Goldberg M, Hayvanovych M, Magdon-Ismail M, Szymanski BK, Wallace WA., Williams GM (2010) Measuring behavioral trust in social networks. In: Proc. Intl. Conf. on Intelligence and Security Informatics, pp 150–152

  • Adalı S, Magdon-Ismail M, Sisenda F (2012) Actions speak as loud as words: predicting relationships from social behavior data. In: Proceedings of the WWW Conference

  • Aharony N, Pan W, Ip C, Khayal I, Pentland A (2011) Socialfmri: investigating and shaping social mechanisms in the real world. Pervasive Mobile Comput 7(6):643–659

    Article  Google Scholar 

  • Asendorpf J, Wilpers S (1998) Personality effects on social relationship. J Personal Soc Psychol 74(6): 1531–1544

    Article  Google Scholar 

  • Barrick MR, Mount MK (1991) The big five personality dimensions and job performance: a meta-analysis. Personnel Psychol 44(1):1–26

    Article  Google Scholar 

  • Burt RS, Jannotta JE, Mahoney JT (1998) Personality correlates of structural holes. Soc Netw 20(1):63 – 87

    Article  Google Scholar 

  • Catanese S, Ferrara E, Fiumara G (2013) Forensic analysis of phone call networks. Soc Netw Anal Min 3(1):15–33. doi:10.1007/s13278-012-0060-1

    Google Scholar 

  • Center P (2012) Americans and text messaging. http://pewinternet.org/Reports/2011/Cell-Phone-Texting-2011.aspx.. Accessed 29 Nov 2012

  • De Raad B (2000) The big five personality factors: the psycholexical approach to personality. Hogrefe & Huber, Göttingen

  • Digman J (1990) Personality structure: emergence of the five-factor model. Annu Rev Psychol 41(1):417–440

    Article  Google Scholar 

  • Eagle N (2008) Behavioral inference across cultures Using telephones as a cultural lens. Intell Syst IEEE 23(4):62–64 (2008)

    Article  Google Scholar 

  • Eagle N, Pentland A, Lazer D (2009a) Inferring friendship network structure by using mobile phone data. Proc Natl Acad Sci 106(36):15274–15278

    Google Scholar 

  • Eagle N, Pentland A, Lazer D (2009b) Inferring social network structure using mobile phone data. Proc Natl Acad Sci (PNAS) 106(36):15274–15278

    Google Scholar 

  • Ferri F, Grifoni P, Guzzo T (2012) New forms of social and professional digital relationships: the case of facebook. Soc Netw Anal Min 2(2):121–137 doi:10.1007/s13278-011-0038-4

  • Golbeck J, Robles C, Edmondson M, Turner K (2011) Predicting personality from twitter. In: Proceedings of the 3rd IEEE Intl. Conf. on Social Computing, pp 149–156

  • Golbeck J, Robles C, Turner K (2011) Predicting personality with social media. In: Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems, CHI EA ’11, pp 253–262

  • Goldberg L (1982) From Ace to Zombie: some explorations in the language of personality. Adv Personal Assess 1:203–234

    Google Scholar 

  • Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten I (2009) The WEKA data mining software: an update. ACM SIGKDD Explor Newsl 11(1):10–18

    Article  Google Scholar 

  • Hansen MT (1999) The search-transfer problem: the role of weak ties in sharing knowledge across organization subunits. Adm Sci Quart 44(1):82 – 111

    Article  Google Scholar 

  • John O. (1990) The "Big Five" factor taxonomy: dimensions of personality in the natural language and in questionnaires. Handb Personal: Theory Res 14:66–100

    Google Scholar 

  • John O, Donahue E, Kentle R (1991) The big five inventoryversions 4a and 54. University of California, Berkeley, Institute of Personality and Social Research

  • Klein K, Lim B, Saltz J, Mayer DM (2004) How do they get there? an examination of the antecedents of centrality in team networks. Acad Manag J 47(6):952–963

    Article  Google Scholar 

  • Kosinski M, Stillwell D, Graepel T (2013) Private traits and attributes are predictable from digital records of human behavior. Proc Natl Acad Sci 110(15):5802–5805. doi:10.1073/pnas.1218772110. http://www.pnas.org/content/110/15/5802.abstract

  • Mairesse F, Walker M, Mehl M, Moore R (2007) Using linguistic cues for the automatic recognition of personality in conversation and text. J Artif Intell Res 30(1):457–500

    MATH  Google Scholar 

  • McCrae R (1989) Why I advocate the five-factor model: joint factor analyses of the NEO-PI with other instruments. Personality psychology: recent trends and emerging directions, pp 237–245. doi:10.1007/978-1-4684-0634-4_18

  • McCrae R, Costa P (1990) Personality in adulthood: a five-factor theory perspective. The Guilford Press, New York

  • McCrae R., John O. (1992) An introduction to the five-factor model and its applications. J Personal 60(2):175–215

    Article  Google Scholar 

  • McPherson M, Smith-Lovin L, Cook JM (2001) Birds of a feather: homophily in social networks. Annu Rev Sociol 27:415–444

    Article  Google Scholar 

  • Moskowitz DC, Zuroff DC (2005) Robust predictors of flux, pulse, and spin. J Res Personal 39:130147

    Google Scholar 

  • Moskowitz DS, Zuroff DC (2004) Flux, pulse, and spin: dynamic additions to the personality lexicon. J Personal So Psychol 86(6):880893

    Google Scholar 

  • Peabody D, De Raad B (2002) The substantive nature of psycholexical personality factors: a comparison across languages. J Personal Soc Psychol 83(4):983–997

    Article  Google Scholar 

  • Pennebaker J, Francis M, Booth R (2001) Linguistic inquiry and word count: LIWC 2001. Lawrence Erlbaum Associates, Mahway

  • Pennebaker J, King L (1999) Linguistic styles: language use as an individual difference. J Personal Soc Psychol 77(6):1296–1312

    Article  Google Scholar 

  • Quercia D, Kosinski M, Stillwell D, Crowcroft J (2011) Our twitter profiles, our selves: predicting personality with twitter. In: Privacy, security, risk and trust (passat), 2011 ieee third international conference on and 2011 ieee third international conference on social computing (socialcom), IEEE, pp 180–185

  • Schmitt D, Allik J, McCrae R, Benet-Martinez V (2007) The geographic distribution of Big Five personality traits: patterns and profiles of human self-description across 56 nations. J Cross Cult Psychol 38(2):173

    Article  Google Scholar 

  • Sheldon KM, Ryan RM, Rawsthorne LJ, Ilardi B (1997) Trait self and true self: cross-role variation in the big-five personality traits and its relations with psychological authenticity and subjective well-being. J Personal Soc Psychol 73(6):1380–1393

    Article  Google Scholar 

  • Sherman RA, Nave CS, Funder DC (2012) Properties of persons and situations related to overall and distinctive personality-behavior congruence. J Res Personal 46(1):87 – 101

    Article  Google Scholar 

  • Staiano J, Lepri B, Aharony N, Pianesi F, Sebe N, Pentland A (2012) Friends don’t lie: inferring personality traits from social network structure. In: Proceedings of the 2012 ACM Conference on Ubiquitous Computing, UbiComp ’12, pp 321–330. ACM, New York, NY, USA. doi:10.1145/2370216.2370266

  • Staiano J, Lepri B, Aharony N, Pianesi F, Sebe N, Pentland S (2012) Friends don’t lie—inferring personality traits from social network structure. In: Proceedings of UbiComp’12

  • Tchuente D, Canut MF, Jessel N, Peninou A, Sèdes F (2013) A community-based algorithm for deriving users’ profiles from egocentrics networks: experiment on facebook and dblp. Soc Netw Anal Min, pp 1–17. doi:10.1007/s13278-013-0113-0

  • Tett RP, Burnett DD (2003) A personality trait-based interactionist model of job performance. J Appl Psychol 88(3):500 –517

    Article  Google Scholar 

  • Tupes E, Christal R (1992) Recurrent personality factors based on trait ratings. J Personal 60(2):225–251

    Article  Google Scholar 

  • Wang C, Lizardo O, Hachen D, Strathman A, Toroczkai Z, Chawla NV (2012) A dyadic reciprocity index for repeated interaction networks. Netw Sci 1:31–48

    Article  Google Scholar 

  • Wuchty S, Uzzi B (2011) Human communication dynamics: a study of the agreement between self-reported and email derived social networks. PLoS One 6(11):e26972. doi:10.1371/journal.pone.0026972

Download references

Acknowledgments

Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-09-2-0053. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the US Government. The US Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sibel Adalı.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Adalı, S., Golbeck, J. Predicting personality with social behavior: a comparative study. Soc. Netw. Anal. Min. 4, 159 (2014). https://doi.org/10.1007/s13278-014-0159-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s13278-014-0159-7

Keywords

Navigation