@inproceedings{attri-etal-2025-feel,
title = "Why We Feel What We Feel: Joint Detection of Emotions and Their Opinion Triggers in {E}-commerce",
author = "Attri, Arnav and
Attri, Anuj and
Banerjee, Suman and
Patil, Amey and
Chelliah, Muthusamy and
Garera, Nikesh and
Bhattacharyya, Pushpak",
editor = "Christodoulopoulos, Christos and
Chakraborty, Tanmoy and
Rose, Carolyn and
Peng, Violet",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-emnlp.295/",
pages = "5515--5532",
ISBN = "979-8-89176-335-7",
abstract = "Customer reviews on e-commerce platforms capture critical affective signals that drive purchasing decisions. However, no existing research has explored the joint task of emotion detection and explanatory span identification in e-commerce reviews - a crucial gap in understanding what triggers customer emotional responses. To bridge this gap, we propose a novel joint task unifying Emotion detection and Opinion Trigger extraction (EOT), which explicitly models the relationship between causal text spans (opinion triggers) and affective dimensions (emotion categories) grounded in Plutchik{'}s theory of 8 primary emotions.In the absence of labeled data, we introduce EOT-X, a human-annotated collection of 2,400 reviews with fine-grained emotions and opinion triggers. We evaluate 23 Large Language Models (LLMs) and present EOT-DETECT, a structured prompting framework with systematic reasoning and self-reflection. Our framework surpasses zero-shot and chain-of-thought techniques, across e-commerce domains."
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%0 Conference Proceedings
%T Why We Feel What We Feel: Joint Detection of Emotions and Their Opinion Triggers in E-commerce
%A Attri, Arnav
%A Attri, Anuj
%A Banerjee, Suman
%A Patil, Amey
%A Chelliah, Muthusamy
%A Garera, Nikesh
%A Bhattacharyya, Pushpak
%Y Christodoulopoulos, Christos
%Y Chakraborty, Tanmoy
%Y Rose, Carolyn
%Y Peng, Violet
%S Findings of the Association for Computational Linguistics: EMNLP 2025
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-335-7
%F attri-etal-2025-feel
%X Customer reviews on e-commerce platforms capture critical affective signals that drive purchasing decisions. However, no existing research has explored the joint task of emotion detection and explanatory span identification in e-commerce reviews - a crucial gap in understanding what triggers customer emotional responses. To bridge this gap, we propose a novel joint task unifying Emotion detection and Opinion Trigger extraction (EOT), which explicitly models the relationship between causal text spans (opinion triggers) and affective dimensions (emotion categories) grounded in Plutchik’s theory of 8 primary emotions.In the absence of labeled data, we introduce EOT-X, a human-annotated collection of 2,400 reviews with fine-grained emotions and opinion triggers. We evaluate 23 Large Language Models (LLMs) and present EOT-DETECT, a structured prompting framework with systematic reasoning and self-reflection. Our framework surpasses zero-shot and chain-of-thought techniques, across e-commerce domains.
%U https://aclanthology.org/2025.findings-emnlp.295/
%P 5515-5532
Markdown (Informal)
[Why We Feel What We Feel: Joint Detection of Emotions and Their Opinion Triggers in E-commerce](https://aclanthology.org/2025.findings-emnlp.295/) (Attri et al., Findings 2025)
ACL