Professor of Economics and Director of ICES Daniel Houser has a new paper in the latest issue of the journal Experimental Economics.
The article, “Classification of Natural Language Messages Using a Coordination Game,” was co-authored with Professor Erte Xiao, a former ICES graduate student and currently Assistant Professor in the Department of Social and Decision Sciences at Carneige Mellon University.
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.