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.- Anthology ID:
- 2023.findings-emnlp.186
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2023
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Houda Bouamor, Juan Pino, Kalika Bali
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2822–2840
- Language:
- URL:
- https://aclanthology.org/2023.findings-emnlp.186
- DOI:
- 10.18653/v1/2023.findings-emnlp.186
- Cite (ACL):
- Gerard Yeo and Kokil Jaidka. 2023. The PEACE-Reviews dataset: Modeling Cognitive Appraisals in Emotion Text Analysis. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 2822–2840, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- The PEACE-Reviews dataset: Modeling Cognitive Appraisals in Emotion Text Analysis (Yeo & Jaidka, Findings 2023)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2023.findings-emnlp.186.pdf