Comparing English and Russian humour perceptions through signature analysis

Faisal L Kadri, Ekaterina N. Zakharenko


Signature analysis is a statistical technique introduced in the 1940s in order to identify groups of statistical measures to identify aircraft from radar reflections. Other applications include particle identification in nuclear physics and dark matter location in astrophysics. Humour appreciation, or funniness scores, are empirical measures of perceived humour. Two questionnaires, one in English, the other its translation into Russian, were made available online. Each had 96 humorous sentences or jokes. The sentences were classified empirically according to four age trends. Signatures of the four classes of sentences are calculated from participant scores in six age groups. The original scores will be available to researchers for verification and further investigation from either author. The use of signature analysis in this work involves the comparison of a sentence profile with the signature of its class or category; if the profile meets a strict criterion of errors then it can be described as a best predictor of its class. One notable finding from signature analysis is the existence of offsets: displacement of a sentence profile from its type signature. We suggest that offset values are direct measures of humorousness without reference to context. In this analysis, the profiles of the Russian and English sentences are compared to each other and their graphical differences are interpreted including offsets.


humour, cybernetics, signature analysis, English, Russian

Full Text:



Craik, K. H., Lampert, M. D., & A.J. Nelson, (1996). ‘Sense of humor and styles of everyday humorous conduct’. Humor: International Journal of Humor Research 9, pp. 273-302.

Das Gupta, S. ed. (1994). Selected P+apers of C. R. Rao. New York: Wiley.

Kadri, F.L. (2011). ‘The design and validation of an artificial personality’, Kybernetes 40(7/8), pp. 1078-1089.

Kadri, F.L. (2013). ‘Towards compatibility between artificial and psychometric personality models’. Kybernetes 42 (3), pp. 497-505.

Kadri, F. L. (2014). ‘Understanding and learning to reconcile differences between disciplines through constructing an artificial personality’. Kybernetes 43 (9/10), pp.1338-1345.

Kadri, F. L. (2015). ‘The cybernetics of humour: Introducing signature analysis to humour research’. Kybernetes 44 (8/9), pp. 1274-1283.

Martin, R. A. (1996). ‘The Situational Humor Response Questionnaire (SHRQ) and Coping Humor Scale (CHS): A decade of research findings’. Humor: International Journal of Humor Research 9, pp. 251–272.

Martin, R. A. Puhlik-Doris, P. Larsen, G. Gray, J. and K. Weir, K. (2003). ‘Individual differences in uses of humor and their relationship to psychological well-being: Development of the humor styles questionnaire’. Journal of Research in Personality 37, pp. 48-75.

Mueller, L. and Ruch, W. (2011) ‘Humor and strengths of character’. The Journal of Positive Psychology 6, pp. 368-376.

Ruch, W (2012). ‘Towards a new structural model of the sense of humor: Preliminary findings’, in AAAI Technical Report FS-12-02, Artificial Intelligence of Humor.

Schmidt-Hidding, W. (1963). Europäische Schlüsselwörter. Band I: Humor und Witz. [European key terms. Volume I: Humor and wit]. Munich, Germany: Huber.



  • There are currently no refbacks.

Publication ethics and malpractice statement