Affective Text: Generation Strategies and Emotion Measurement Issues

In affective natural language generation (NLG) a major aim is to be able to influence the emotional effects evoked in the addressee through the intelligent use of language. While previous work has shown that varying the form of the language, while keeping the content the same, can have a measurable effect on the emotions of the addressee, we report here on work which investigated which linguistic techniques to give the text a more or less positive slant contribute to these emotional effects. We report on three studies in which texts that gave positive feedback on an IQ test performance were tested for emotional effects on the recipient. The first study followed a comparison method on the sentence level, and the second study compared the texts as a whole. In both of these, participants were asked to rate the emotional effects that they thought the texts would have. On the other hand, in the third study different types of feedback were evaluated in a context of use, where participants...

• Type: Journal
• Year: 2011
• Where: FLAIRS
• Authors: Ielka van der Sluis, Chris Mellish, Gavin Doherty
• Keywords: Artificial Intelligence, FLAIRS 2011, Iq Test, Linguistic Techniques, Natural Language Generation