Evaluation Metrics for Persuasive NLP with Google AdWords

Marco Guerini, Carlo Strapparava, Oliviero Stock

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Abstract
Evaluating systems and theories about persuasion represents a bottleneck for both theoretical and applied fields: experiments are usually expensive and time consuming. Still, measuring the persuasive impact of a message is of paramount importance. In this paper we present a new ``cheap and fast'' methodology for measuring the persuasiveness of communication. This methodology allows conducting experiments with thousands of subjects for a few dollars in a few hours, by tweaking and using existing commercial tools for advertising on the web, such as Google AdWords. The central idea is to use AdWords features for defining message persuasiveness metrics. Along with a description of our approach we provide some pilot experiments, conducted both with text and image based ads, that confirm the effectiveness of our ideas. We also discuss the possible application of research on persuasive systems to Google AdWords in order to add more flexibility in the wearing out of persuasive messages.
Anthology ID:
L10-1142
Volume:
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)
Month:
May
Year:
2010
Address:
Valletta, Malta
Editors:
Nicoletta Calzolari, Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Mike Rosner, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2010/pdf/209_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Marco Guerini, Carlo Strapparava, and Oliviero Stock. 2010. Evaluation Metrics for Persuasive NLP with Google AdWords. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), Valletta, Malta. European Language Resources Association (ELRA).
Cite (Informal):
Evaluation Metrics for Persuasive NLP with Google AdWords (Guerini et al., LREC 2010)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2010/pdf/209_Paper.pdf
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