Multi-feature fusion-based consumer perceived risk prediction and its interpretability study.
E-commerce faces challenges such as content homogenization and high perceived risk among users. This paper aims to predict perceived risk in different contexts by analyzing review content and website information. Based on a dataset containing 262,752 online reviews, we employ the KeyBERT-TextCNN mod...
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Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2025-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0316277 |
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