A Survey on Fake Review Detection: From Pre-trained Language Models to Large Language Models
Online reviews shape consumer decisions, platform governance, and corporate reputation.Fake reviews compromise this information channel by injecting deceptive evidence into rating systems, recommendation pipelines, and public trust mechanisms.The rise of large language models, or LLMs, has changed the problem in two directions.LLMs can generate fluent and context-aware deceptive reviews, while pre-trained language models, or PLMs, and LLMs also provide stronger semantic representations for detection.This survey reviews fake review detection from an information fusion perspective, covering 211 studies published from 2018 to early 2026.We organize existing work by evidence source and fusion...
| Authors | Fanji Yang, Huiyao Chen, Xi Yu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 12 September 2026 |
| Last updated at source | 12 September 2026 |
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