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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.04708 |
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| _version_ | 1866909677309132800 |
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| author | Attri, Arnav Attri, Anuj Bhattacharyya, Pushpak Banerjee, Suman Patil, Amey Chelliah, Muthusamy Garera, Nikesh |
| author_facet | Attri, Arnav Attri, Anuj Bhattacharyya, Pushpak Banerjee, Suman Patil, Amey Chelliah, Muthusamy Garera, Nikesh |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_04708 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Why We Feel What We Feel: Joint Detection of Emotions and Their Opinion Triggers in E-commerce Attri, Arnav Attri, Anuj Bhattacharyya, Pushpak Banerjee, Suman Patil, Amey Chelliah, Muthusamy Garera, Nikesh Computation and Language I.2.7; H.3.1; I.2.6 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. |
| title | Why We Feel What We Feel: Joint Detection of Emotions and Their Opinion Triggers in E-commerce |
| topic | Computation and Language I.2.7; H.3.1; I.2.6 |
| url | https://arxiv.org/abs/2507.04708 |