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Affective Language

Project Number: 360-89-050 

Project Manager: Dr. Mariët Theune

Project website:


This projects aims to investigate (1) how the emotional states of speakers influence the language they produce and (2) how the influence of emotion on language production can be modeled in computational tools for affective natural language generation. Specifically, we ask both whether content selection (“deciding what to say”) and message formulation (“deciding how to say it”) are affected by emotional appraisals of the language user. This will be studied in a series of experiments, zooming in on referential communication; for example, we study whether happy speakers are more likely to describe people based on positive properties (“the smiling girl”) even though other properties such as hair color (“the blond girl”) are equally effective. The experimental findings will feed into the development of a novel automatic news report generation tool that can adjust the message depending on the emotion it intended to reflect (e.g., a report of the same match from the perspective of a losing team will be different from the report for the winning team). The application is developed with support from two interested parties from industry (Sanoma Media, in The Netherlands, and ARRIA, in the UK) that have expressed an interest in tools for the automatic generation of affective language. The findings from all three projects will be relevant for psycholinguistics, affective scientists, computational linguistics, and those working in the area of affective natural language generation. All our results will be made publicly availably (open source, open access).

Project duration: 1 November 2015 - 1 November 2019

Project budget: 733.8 k-€ funding

Number of person/months: 132

Project Coordinator: University of Tilburg

Participants: University of Tilburg, UT

Project budget CTIT: 220 k-€ funding

Number of person/months CTIT: 1.2 fte

Involved groups: Human Media Interaction