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In this study we collect and annotate human-human role-play dialogues in thedomain of weight management. There are two roles in the conversation: the"seeker" who is looking for ways to lose weight and the "helper" who providessuggestions to help the "seeker" in their weight loss journey. The chatdialogues collected are then annotated with a novel annotation scheme inspiredby a popular health behavior change theory called "trans-theoretical model ofhealth behavior change". We also build classifiers to automatically predict theannotation labels used in our corpus. We find that classification accuracyimproves when oracle segmentations of the interlocutors' sentences are providedcompared to directly classifying unsegmented sentences.

A Dialogue Annotation Scheme for Weight Management Chat using the Trans-Theoretical Model of Health Behavior Change