Conversation Peculiarities of People with Different Verbal Intelligence
In this paper we present a study on language use peculiarities of people with different verbal intelligence. The work is based on a corpus containing dialogues about the same topic and verbal intelligence scores of the dialogue participants. Content and style words were extracted from the transcribed dialogues using the LIWC dictionary. Features characterizing the dialogue flow (number of short and long utterances, successful and unsuccessful interruptions, repeated and incomplete words, etc.) were also calculated. Using a simple one-way analysis of variance the mean values of these features for test persons with higher and lower verbal intelligence were compared.
KeywordsTest Person Content Word Verbal Intelligence Unique Word Dialogue Partner
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This work is partly supported by the DAAD (German Academic Exchange Service).
Parts of the research described in this article are supported by the Transregional Collaborative Research Centre SFB/TRR 62 ”Companion-Technology for Cognitive Technical Systems” funded by the German Research Foundation (DFG).
- 1.G. Celeux and J. Diebolt. 1987. The EM and the SEM algorithms for mixtures: Statistical and numerical aspects. Lingua, Rapports de Recherche(641).Google Scholar
- 2.A.T. Cianciolo, T.J. Sternberg. 2004. Intelligence: a Brief History. Blackwell Publishing.Google Scholar
- 3.Encyclopedia of Leadership. 2004. Editors: G.R. Goethals, G.J. Sorenson, J.M. Bruns. Sage Publications (CA).Google Scholar
- 4.A. Leffler, D.L. Gillespie, and C. Conaty. 1982. Their effects of status differentiation on nonverbal behaviour. Social Psychology Quarterly, 45(3).Google Scholar
- 5.A. Logsdon Learning Disabilities. http://learningdisabilities.about.com/.
- 6.E. Mergenthaler. 1996. Emotion-abstraction patterns in verbatim protocols: A new way of describing psychotherapeutic processes. Journal of Consulting and Clinical Psychology, 6(64).Google Scholar
- 7.Y. Ohsawa, N. Matsumura, and M. Ishizuka. 2002. Influence diffusion model in text-based communication. In Proc. of the eleventh world wide web conference.Google Scholar
- 8.R. Rienks and D. Heylen. 2005. Dominance detection in meetings using easily obtainable features. In Revised Selected Papers of the 2nd Joint Workshop on Multimodal Interaction and Related Machine Learning Algorithms, pages 76– 86.Google Scholar
- 9.Y.R. Tausczik and J.W. Pennebaker. in press. The psychological meaning of words: Liwc and computerized text analysis methods. Journal of Language and Social Psychology.Google Scholar
- 10.D. Wechsler. 1982. Handanweisung zum Hamburg-Wechsler-Intelligenztest fuer Erwachsene (HAWIE). Separatdr., Bern; Stuttgart; Wien, Huber.Google Scholar
- 11.M.Wolf, A. B. Horn, M. R. Mehl, and S. Haug. 2008. Aequivalenz und robustheit der deutschen version des linguistic inquiry and word count. Diagnostica, 54, Heft 2:85–98.Google Scholar
- 12.K. Zablotskaya, S.Walter, andW. Minker. 2010. Speech data corpus for verbal intelligence estimation. In Proceedings of LREC’10, May.Google Scholar