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Sentiment Variations in Text for Persuasion Technology

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Persuasive Technology (PERSUASIVE 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8462))

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Abstract

Accurate wording is essential in persuasive verbal communication. Through it speakers can provide an affective connotation to the text and reveal their disposition or induce a similar disposition on the recipient. All this is apparent in persuasion texts par excellence, such as political speech and advertisement. Automatic sentiment variations of existing linguistic expressions open the way to promising applications, yet it is a challenging problem. In this paper we describe a system which takes up this challenge, together with a framework for evaluating the persuasiveness of the newly produced expressions.

This work respects professional code of conduct and does not qualify as coercion or deceit.

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Author information

Authors and Affiliations

  1. Trento RISE, Trento, Italy

    Lorenzo Gatti & Marco Guerini

  2. FBK-irst, Trento, Italy

    Oliviero Stock & Carlo Strapparava

Authors
  1. Lorenzo Gatti
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  2. Marco Guerini
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  3. Oliviero Stock
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  4. Carlo Strapparava
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Editor information

Editors and Affiliations

  1. Human Technology Lab, Department of General Psychology, University of Padova, Via Venezia, 8, 35131, Padova, Italy

    Anna Spagnolli

  2. Human-Computer Interaction Lab, University of Udine, via delle Scienze 206, 33100, Udine, Italy

    Luca Chittaro

  3. Department of General Psychology, University of Padova, Italy

    Luciano Gamberini

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© 2014 Springer International Publishing Switzerland

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Gatti, L., Guerini, M., Stock, O., Strapparava, C. (2014). Sentiment Variations in Text for Persuasion Technology. In: Spagnolli, A., Chittaro, L., Gamberini, L. (eds) Persuasive Technology. PERSUASIVE 2014. Lecture Notes in Computer Science, vol 8462. Springer, Cham. https://doi.org/10.1007/978-3-319-07127-5_10

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  • DOI: https://doi.org/10.1007/978-3-319-07127-5_10

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07126-8

  • Online ISBN: 978-3-319-07127-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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