Quality Assessment of Tourist Generated Contents: A Large Language Model Approach
文献类型：期刊论文
| 作者 | Gao, Jialiang2; Peng, Peng3; Claramunt, Christophe1,3; Lu, Feng3 |
| 刊名 | WEB AND WIRELESS GEOGRAPHICAL INFORMATION SYSTEMS, W2GIS 2025
 |
| 出版日期 | 2026 |
| 卷号 | 15946页码:31-41 |
| 关键词 | Quality Assessment User Generated Content Large LanguageModel |
| ISSN号 | 0302-9743 |
| DOI | 10.1007/978-3-032-01723-9_3 |
| 产权排序 | 2 |
| 文献子类 | Proceedings Paper |
| 英文摘要 | The exponential growth of tourist-generated content necessitates efficient quality assessment frameworks to address inherent challenges of information reliability and analytical scalability. This study pioneers a Large Language Model (LLM)-driven approach, integrating supervised fine-tuning with low-rank adaptation and structured prompt engineering to enable multi-dimensional quality evaluation. Covering 485,930 reviews from three major platforms-MaFengWo, TripAdvisor, and Ctrip-the framework achieves superior performance (RMSE = 0.56, NDCG@K = 0.88) in generating accurate quality scores and detailed analytical rationales. Spatial-temporal-semantic analyses reveal platform-specific quality patterns: MFW exhibits stable temporal cointegration and prominent spatial centrality, TripAdvisor demonstrates simplified core-periphery structures, while Ctrip presents dynamic multicentricity. Heterogeneous network analysis further identifies the behavioral regularities of high-reliability users through a randomwalk algorithm. The study advances tourism informatics by resolving scalability limitations of manual coding while providing actionable insights for platform governance, including targeted moderation and incentive mechanisms. This paradigm highlights LLMs' transformative potential in operationalizing tourist-generated content quality assessment at scale, bridging theoretical rigor with practical applicability within digital tourism ecosystems. |
| URL标识 | 查看原文 |
| WOS关键词 | ONLINE REVIEWS ; HELPFUL |
| WOS研究方向 | Computer Science ; Telecommunications |
| 语种 | 英语 |
| WOS记录号 | WOS:001576340100003 |
| 出版者 | SPRINGER INTERNATIONAL PUBLISHING AG |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/219738]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Peng, Peng |
| 作者单位 | 1.Naval Acad Res Inst, F-29240 Lanveoc, France 2.Fuzhou Univ, Acad Digital China Fujian, Fuzhou 350108, Peoples R China; 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Gao, Jialiang,Peng, Peng,Claramunt, Christophe,et al. Quality Assessment of Tourist Generated Contents: A Large Language Model Approach[J]. WEB AND WIRELESS GEOGRAPHICAL INFORMATION SYSTEMS, W2GIS 2025,2026,15946:31-41. |
| APA | Gao, Jialiang,Peng, Peng,Claramunt, Christophe,&Lu, Feng.(2026).Quality Assessment of Tourist Generated Contents: A Large Language Model Approach.WEB AND WIRELESS GEOGRAPHICAL INFORMATION SYSTEMS, W2GIS 2025,15946,31-41. |
| MLA | Gao, Jialiang,et al."Quality Assessment of Tourist Generated Contents: A Large Language Model Approach".WEB AND WIRELESS GEOGRAPHICAL INFORMATION SYSTEMS, W2GIS 2025 15946(2026):31-41. |
入库方式： OAI收割
来源：地理科学与资源研究所
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