Just the Way You Chat: Linking Personality, Style and Recognizability in Chats
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.
Keywordschat analysis personality traits authorship attribution
Unable to display preview. Download preview PDF.
- 3.Orebaugh, A., Allnutt, J.: Classification of instant messaging communications for forensics analysis. Social Networks, 22–28 (2009)Google Scholar
- 6.Knapp, M.L.: Nonverbal communication in human interaction, 8th edn., January 1. Cengage Learning (2013)Google Scholar
- 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
- 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.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.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
- 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.Bolle, R., Connell, J., Pankanti, S., Ratha, N., Senior, A.: Guide to Biometrics. Springer (2003)Google Scholar
- 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