Speaker: A/Prof Stephanie Wang

Affiliation: University of Pittsburgh

Location: Level 6 Boardroom, Colin Clark Building (#39), UQ St Lucia Campus.

Online via Zoom: https://uqz.zoom.us/j/84008636651

Abstract

Models of communication, deliberation, and persuasion highlight message quality, i.e., the credibility of a message, to be a major determinant of persuasiveness. The recent literature on persuasion and narratives argues that convincing messages are backed up by stories or models, i.e., by arguments. As yet, there is no common empirical measure of message persuasiveness. We propose counting arguments used to support claims as a simple, context-independent empirical measure of message persuasiveness. We show that this measure is easy to implement using simple Natural Language Processing and Machine Learning techniques, and that it has predictive value with regard to changes in beliefs and behavior. In a two-wave experiment, we collected voting intentions and text data from randomized chat interactions before a ballot and voting choices after a ballot. We find that the increased use of arguments induces more vote changes.

About the presenter's meeting

If you would like to meet with A/Prof Wang, please contact Dr Zachary Breig

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Venue

Colin Clark Building (#39)
Room: 
Level 6 Boardroom (629)