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Báo cáo khoa học: "Measuring Conformity to Discourse Routines in Decision-Making Interactions"

In an effort to develop measures of discourse levelmanagementstrategies,this study examines a measure of the degree to which decisionmaking interactions consist of sequences of utterance functions that are linked in a decisionmaking routine. The measure is applied to 100 dyadic interactions elicited in both face-to-face and computer-mediated environments with systematic variation of task complexity and message-window size. Every utterance in the interactions is coded according to a system that identifies decision-makmg functions and other routine functions of utterances. . | Measuring Conformity to Discourse Routines in Decision-Making Interactions Sherri L. Condon Claude G. Cech William R. Edwards Department of English Department of Psychology Center for Advanced Computer Studies condo@usl.edu cech@usl.edu wre@cacs.usl.edu University of Southwestern Louisiana Université des Acadiens Lafayette LA 70504 Abstract In an effort to develop measures of discourse level management strategies this study examines a measure of the degree to which decisionmaking interactions consist of sequences of utterance functions that are linked in a decisionmaking routine. The measure is applied to 100 dyadic interactions elicited in both face-to-face and computer-mediated environments with systematic variation of task complexity and message-window size. Every utterance in the interactions is coded according to a system that identifies decision-making functions and other routine functions of utterances. Markov analyses of die coded utterances make it possible to measure the relative frequencies with which sequences of 2 and 3 utterances trace a path in a Markov model of the decision routine. These proportions suggest that interactions in all conditions adhere to the model although we find greater conformity in the computer-mediated environments which is probably due to increased processing and attentional demands for greater efficiency. Hie results suggest that measures based on Markov analyses of coded interactions can provide useful measures for comparing discourse level properties for correlating discourse features with other textual features and for analyses of discourse management strategies. Introduction Increasingly research in computational linguistics has contributed to knowledge about the organization and processing of human interaction through quantitative analyses of annotated texts and dialogues e g. Carletta et al. 1997 Cohen et al. 1990 Maier et al. 1997 Nakatani et al. 1995 Passonneau 1996 Walker 1996 . This program of research presents .