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Corpus Pragmatics

, Volume 3, Issue 4, pp 327–361 | Cite as

A Sociolinguistic Analysis of Emotives

  • Martin SchweinbergerEmail author
Original Paper

Abstract

This study details a replicable method for annotating emotionality of natural language that can be used in sociopragmatic, corpus-based analyses of discourse. A case study uses a type of sentiment analysis based on the crowd-sourced Word-Emotion Association Lexicon to investigate the social stratification of emotives, i.e. words associated with one of eight core emotions (ANGER, ANTICIPATION, FEAR, DISGUST, JOY, SADNESS; SURPRISE, and TRUST). The sentiment analysis is applied to dialogue data taken from the Irish component of the International Corpus of English and emotion scores provided by the sentiment analysis are correlated with the age and gender of speakers, the audience size, conversation type (same- vs. mixed gender conversation), dialogue setting (private vs. public), and part-of speech. The results of mixed-effects binomial regression models show that speakers use FEAR emotives significantly more frequently in public settings while JOY, DISGUST, and SURPRISE emotives are used more in private settings. In addition, men are significantly more likely to use ANGER and FEAR emotives, while women show higher rates of JOY emotives. Speakers aged 33 and older are more likely to use TRUST emotives compared with younger speakers. The results challenge common gendered social stereotypes according to which emotional language is associated with young women in particular. In contrast, the study shows that the genders exhibit emotion-specific preferences. In addition, the finding that negative emotions are more frequent in public discourse may indicate a general tendency even in apolitical conversation. However, the socio-political context in which the data were gathered has to be taken into account. It is highly likely that the linguistic expression of emotion was substantially affected by the communal tensions during the Northern Ireland conflict and findings should thus be treated with care not be naively generalized.

Keywords

Sentiment analysis Emotion language Sociolinguistics Gender differences Emotives 

Notes

Compliance with Ethical Standards

Conflict of interest

The author declares that there are no conflicts of interest.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Languages and CulturesThe University of QueenslandSt LuciaAustralia

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