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Classification of natural language messages using a coordination game

Published online by Cambridge University Press:  14 March 2025

Daniel Houser  and
Erte Xiao
Daniel Houser*
Affiliation:
George Mason University, Fairfax, USA
Erte Xiao*
Affiliation:
Carnegie Mellon University, Pittsburgh, USA
*
e-mail: dhouser@gmu.edu
e-mail: exiao@andrew.cmu.edu
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Abstract

The role of natural language communication in economic exchange has been the focus of substantial experimental analysis. Recently, scholars have taken the important step of investigating whether certain types of communication (e.g., promises) might affect decisions differently than other types of communication. This requires classifying natural language messages. Unfortunately, no broadly-accepted method is available for this purpose. We here describe a coordination game for classification of natural language messages. The game is similar in spirit to the “ESP” game that has proven successful for the classification of tens of millions of internet images. We compare our approach to self-classification as well as to classifications based on a standard content analysis. We argue that our classification game has advantages over those alternative approaches, and that these advantages might stem from the salient rewards earned by our game's participants.

Keywords

Classification gameNatural languageMessagesCoordination gameExperimental methods

Information

Type
Research Article
Information
Experimental Economics , Volume 14 , Issue 1 , March 2011 , pp. 1 - 14
Copyright
Copyright © Economic Science Association 2010

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Footnotes

Electronic supplementary material The online version of this article (doi: 10.1007/s10683-010-9254-4) contains supplementary material, which is available to authorized users.

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