arXiv:2606. 23701v1 Announce Type: cross Abstract: Qualitative product feedback can reveal nuanced user experiences, but its implicit sentiment is difficult to measure.
By Sherri Weitl-Harms, John Hastings
arXiv:2609.22198v1 Announce Type: new
Abstract: The rapid adoption of large language models (LLMs) creates new opportunities for strategic content generation on online platforms, including potentiall...
By Valeria Lerman, Oren Rigbi, Yaniv Dover
The article surveys fake review detection research, focusing on how pre‑trained language models (PLMs) and large language models (LLMs) influence both the generation of deceptive reviews and their detection. It reviews 211 studies from 2018 to early 2026, categorizing methods by evidence source—such as review text, sentiment, rating behavior, temporal metadata, user‑product graphs, multimodal content, external knowledge, and LLM‑generated signals—and by fusion level. The survey traces the evolution from traditional machine learning to PLM‑based and LLM‑based approaches, evaluates performance on Amazon, Yelp, and OpSpam benchmarks, and highlights open challenges including adversarial generation, cross‑domain transfer, uncertainty‑aware fusion, robustness to missing sources, interpretability, and trustworthy evaluation of AI‑generated deceptive content.
By Fanji Yang (Guizhou University of Finance and Economics), Huiyao Chen (Harbin Institute of Technology), Xi Yu (Guizhou University of Finance and Economics), Meishan Zhang (Harbin Institute of Technology), Xiaohong Xiao (Guizhou University of Commerce), Mingsen Deng (Guizhou University of Finance and Economics)
arXiv:2511. 13480v2 Announce Type: replace-cross Abstract: This study focuses on understanding the complex dynamics between humans and AI systems by analyzing user reviews.
By Parisa Arbab, Xiaowen Fang
arXiv:2607. 24601v1 Announce Type: cross Abstract: Background: Large language models (LLMs) are increasingly used to automate code review, but the reasoning behind their decisions remains hard to understand.
By Zhenhan Gao, Marvin Mu\~noz Bar\'on, Umm-e Habiba, Daniel Graziotin, Stefan Wagner
arXiv:2609.18729v1 Announce Type: cross
Abstract: Consumers increasingly use AI chatbots for advice on what to buy. With companies like OpenAI and Google monetising their AI through advertising, this...
By Lucas G. Uberti-Bona Marin, Thales Bertaglia, Giovanni Astante, Bram Rijsbosch, Gijs van Dijck, Anik\'o Hann\'ak, Gerasimos Spanakis, Konrad Kollnig