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Chapitre D'ouvrage Année : 2021

Applying Behavioural Profiles to Multimodal Discourse Analysis. A Quantitative Analysis of Self-praise Strategies in French and Russian Social-media

Résumé

This study reports the results of a proof-of-principle investigation into the application of the behavioural profile approach to discursive multimodal data. The aim is to demonstrate that a combination of usage-feature analysis and multivariate statistics can be employed to identify discourse patterns integrating both verbal and non-verbal communicative strategies. The case study examines self-praise (boasting) of women (on holidays) on social-media (Instagram) in French and Russian. The assumption is that different causes of pride and/or different languages will result in different strategies of self-praise. The study revealed complex yet coherent patterns across the "type of boast", the "intensity of the pride" and the "discourse strategy" employed. Moreover, many of the interactions were found to be significant despite the relatively small sample size. Having established that this kind of multimodal discursive phenomena can be adequately operationalized for quantitative treatment, extending the principle to include other social dimensions, such as age and gender, should be non-problematic.
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Dates et versions

halshs-03807442 , version 1 (09-10-2022)

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Dylan Glynn, Aliya Gimadieva. Applying Behavioural Profiles to Multimodal Discourse Analysis. A Quantitative Analysis of Self-praise Strategies in French and Russian Social-media. De Gruyter. Cognitive Sociolinguistics Revisited, pp.606-620, 2021, ⟨10.1515/9783110733945-049⟩. ⟨halshs-03807442⟩
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