The PEACE-Reviews dataset: Modeling Cognitive Appraisals in Emotion Text Analysis
Submission Type: Regular Long Paper
Submission Track: Computational Social Science and Cultural Analytics
Submission Track 2: Linguistic Theories, Cognitive Modeling, and Psycholinguistics
Keywords: cognitive appraisals, emotions, language modeling, computational social science
TL;DR: PEACE-Reviews dataset: Annotated autobiographical writing on significant purchases, revealing how cognitive appraisal and emotions interact with consumer behavior and demographic traits, with baseline models for feature prediction.
Abstract: Cognitive appraisal plays a pivotal role in deciphering emotions. Recent studies have delved into its significance, yet the interplay between various forms of cognitive appraisal and specific emotions, such as joy and anger, remains an area of exploration in consumption contexts. Our research introduces the PEACE-Reviews dataset, a unique compilation of annotated autobiographical accounts where individuals detail their emotional and appraisal experiences during interactions with personally significant products or services. Focusing on the inherent variability in consumer experiences, this dataset offers an in-depth analysis of participants' psychological traits, their evaluative feedback on purchases, and the resultant emotions. Notably, the PEACE-Reviews dataset encompasses emotion, cognition, individual traits, and demographic data. We also introduce preliminary models that predict certain features based on the autobiographical narratives.
Submission Number: 2537
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