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Auteurs principaux: Nakayama, Yuki, Hikichi, Koki, Liu, Yun Ching, Hirate, Yu
Format: Preprint
Publié: 2025
Sujets:
Accès en ligne:https://arxiv.org/abs/2512.15151
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author Nakayama, Yuki
Hikichi, Koki
Liu, Yun Ching
Hirate, Yu
author_facet Nakayama, Yuki
Hikichi, Koki
Liu, Yun Ching
Hirate, Yu
contents This paper presents a large-scale corpus of Rakuten Travel Reviews. Our collection contains 7.29 million customer reviews for 16 years, ranging from 2009 to 2024. Each record in the dataset contains the review text, its response from an accommodation, an anonymized reviewer ID, review date, accommodation ID, plan ID, plan title, room type, room name, purpose, accompanying group, and user ratings from six aspect categories, as well as an overall score. We present statistical information about our corpus and provide insights into factors driving data drift between 2019 and 2024 using statistical approaches.
format Preprint
id arxiv_https___arxiv_org_abs_2512_15151
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Rakuten Data Release: A Large-Scale and Long-Term Reviews Corpus for Hotel Domain
Nakayama, Yuki
Hikichi, Koki
Liu, Yun Ching
Hirate, Yu
Computation and Language
This paper presents a large-scale corpus of Rakuten Travel Reviews. Our collection contains 7.29 million customer reviews for 16 years, ranging from 2009 to 2024. Each record in the dataset contains the review text, its response from an accommodation, an anonymized reviewer ID, review date, accommodation ID, plan ID, plan title, room type, room name, purpose, accompanying group, and user ratings from six aspect categories, as well as an overall score. We present statistical information about our corpus and provide insights into factors driving data drift between 2019 and 2024 using statistical approaches.
title Rakuten Data Release: A Large-Scale and Long-Term Reviews Corpus for Hotel Domain
topic Computation and Language
url https://arxiv.org/abs/2512.15151