Just the Way You Chat: Linking Personality, Style and Recognizability in Chats

  • Giorgio Roffo
  • Cinzia Giorgetta
  • Roberta Ferrario
  • Marco Cristani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8749)


Text chatting represents a hybrid type of communication, where textual information is delivered following turn-taking dynamics, which characterize spoken interactions. It is interesting to understand whether special interactional behavior can emerge in chats, similarly as it does in face-to-face exchanges. In this work, we focus on the writing style of individuals, analyzing how it can be recognized given a portion of chat, and how personality comes into play in this scenario. Two interesting facts do emerge: 1) some traits correlate significantly with some characteristics of people’s chatting style, captured by stylometric features; 2) some of such features are very effective in recognizing a person among a gallery of diverse individuals. This seems to suggest that some personality traits could lead people to chat with a particular style, which turns out to be very recognizable. For example, motor impulsiveness gives a significative (negative) correlation with the use of the suspension points (…), that is also one of the most discriminative characteristics in chats. This and other relations emerge on a dataset on 45 subjects, monitored for 3 months, whose personality traits have been analyzed through self-administered questionnaires. What turns out is that chatting seems to be more than just typing.


chat analysis personality traits authorship attribution 


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  1. 1.
    Abbasi, A., Chen, H., Nunamaker, J.F.: Stylometric identification in electronic markets: Scalability and robustness. Journal of Management Information Systems (JMIS) 25(1), 49–78 (2008)CrossRefGoogle Scholar
  2. 2.
    Mairesse, F., Walker, M.A., Mehl, M.R., Moore, R.K.: Using linguistic cues for the automatic recognition of personality in conversation and text. Journal of Artificial Intelligence Research (JAIR) 30, 457–500 (2007)zbMATHGoogle Scholar
  3. 3.
    Orebaugh, A., Allnutt, J.: Classification of instant messaging communications for forensics analysis. Social Networks, 22–28 (2009)Google Scholar
  4. 4.
    Stamatatos, E.: A survey of modern authorship attribution methods. Journal of the Association for Information Science and Technology (JASIST) 60(3), 538–556 (2009)CrossRefGoogle Scholar
  5. 5.
    Zheng, R., Li, J., Chen, H., Huang, Z.: A framework for authorship identification of online messages: Writing-style features and classification techniques. Journal of the Association for Information Science and Technology (JASIST) 57(3), 378–393 (2006)CrossRefGoogle Scholar
  6. 6.
    Knapp, M.L.: Nonverbal communication in human interaction, 8th edn., January 1. Cengage Learning (2013)Google Scholar
  7. 7.
    Roffo, G., Segalin, C., Vinciarelli, A., Murino, V., Cristani, M.: Reading between the turns: Statistical modeling for identity recognition and verification in chats. In: IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2013 (2013)Google Scholar
  8. 8.
    Pennebaker, J.W., King, L.A.: Linguistic styles: language use as an individual difference. Journal of Personality and Social Psychology 77(6), 1296–1312 (1999)CrossRefGoogle Scholar
  9. 9.
    Abbasi, A., Chen, H.: Writeprints: A stylometric approach to identity-level identification and similarity detection in cyberspace. ACM TOIS 26(2), 1–29 (2008)CrossRefGoogle Scholar
  10. 10.
    Iqbal, F., Binsalleeh, H., Fung, B.C.M., Debbabi, M.: A unified data mining solution for authorship analysis in anonymous textual communications. Information Sciences (2011)Google Scholar
  11. 11.
    Gajadhar, J., Green, J.: Open Polytechnic of New Zealand, Open Polytechnic of New Zealand Staff. An Analysis of Nonverbal Communication in an Online Chat Group, Working papers, Open Polytechnic of New Zealand (2003)Google Scholar
  12. 12.
    Walters, M.L., Dautenhahn, K., Boekhorst, R., Koay, K.L., Kaouri, C., Woods, S., Nehaniv, C., Lee, D., Werry, I.: The influence of subjects’ personality traits on personal spatial zones in a human-robot interaction experiment. In: International Workshop on Robot and Human Interactive Communication, RO-MAN 2005, August 13-15, pp. 347–352 (2005)Google Scholar
  13. 13.
    Patton, J.H., Stanford, M.S., Barratt, E.S.: Factor structure of the barratt impulsiveness scale. Journal of Clinical Psychology 51, 768–774 (1995)CrossRefGoogle Scholar
  14. 14.
    Davis, M.H.: A multidimensional approach to individual differences in empathy. JSAS Catalog of Selected Documents in Psychology 10, 85–104 (1980)Google Scholar
  15. 15.
    Bolle, R., Connell, J., Pankanti, S., Ratha, N., Senior, A.: Guide to Biometrics. Springer (2003)Google Scholar
  16. 16.
    Dantcheva, A., Velardo, C., D’angelo, A., Dugelay, J.-L.: Bag of soft biometrics for person identification: New trends and challenges. Mutimedia Tools and Applications (October 2010)Google Scholar
  17. 17.
    Markey, P.M., Wells, S.M.: Interpersonal perception in internet chat rooms. Journal of Research in Personality 36(2), 134–146 (2002)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Giorgio Roffo
    • 1
  • Cinzia Giorgetta
    • 2
  • Roberta Ferrario
    • 2
  • Marco Cristani
    • 1
  1. 1.Università degli Studi di VeronaVeronaItaly
  2. 2.ISTC–CNRPovo (Trento)Italy

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