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The focus of this study is on uncovering distinct variations across different online travel agencies (OTAs) regarding key analytical metrics, including review topics, sentiment and review length on consumer ratings and their implications for research and practice.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>Employing a comparative analysis method, this study analyzed over 11,000 user reviews from a premier boutique hotel in China, gathered from three leading Chinese OTAs. It integrated diverse social media analytics techniques, such as Word Cloud analysis, latent Dirichlet\u00a0allocation (LDA), traditional regression and PLS structural equation modeling multi-group analysis (MGA) to evaluate review characteristics among the OTAs.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The results reveal significant discrepancies in review topics, sentiments, review lengths and their effects on consumer ratings across the OTAs examined. These findings highlight the risks of relying on a solitary data source for making generalizations. To improve the data-driven research\u2019s validity and reliability in hospitality and tourism, the study advises the adoption of multi-source data for a more holistic understanding of consumer sentiments and behaviors.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>By pointing out the methodological limitations of present hospitality and tourism research, this paper emphasizes the challenges of a single-source data-driven analytical approach. It suggests several avenues for enhancing the reliability and validity of future research in the field, marking a significant contribution to methodological advancements in hospitality and tourism studies.<\/jats:p><\/jats:sec>","DOI":"10.1108\/imds-09-2024-0881","type":"journal-article","created":{"date-parts":[[2025,3,24]],"date-time":"2025-03-24T03:59:23Z","timestamp":1742788763000},"page":"1946-1976","source":"Crossref","is-referenced-by-count":2,"title":["Maze of conveniences: re-examining hotel reviews and social media data"],"prefix":"10.1108","volume":"125","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8778-2951","authenticated-orcid":false,"given":"Jiyao","family":"Xun","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4678-9436","authenticated-orcid":false,"given":"Yicheng","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5016-6135","authenticated-orcid":false,"given":"Woon Kian","family":"Chong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3958-0754","authenticated-orcid":false,"given":"Emma P.Y.","family":"Wong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5544-2792","authenticated-orcid":false,"given":"Xiaowei","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2025,3,25]]},"reference":[{"issue":"3","key":"key2025042207255394700_ref001","doi-asserted-by":"publisher","first-page":"422","DOI":"10.1007\/s11747-019-00706-1","article-title":"Conceptualizing the electronic word-of-mouth process: what we know and need to know about eWOM creation, exposure, and evaluation","volume":"48","year":"2020","journal-title":"Journal of the Academy of Marketing Science"},{"issue":"3","key":"key2025042207255394700_ref002","first-page":"377","article-title":"The effect of electronic word of mouth on sales: a meta-analytic review of platform, product, and metric factors","volume":"57","year":"2020","journal-title":"Journal of Marketing Research"},{"key":"key2025042207255394700_ref003","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.inffus.2015.08.005","article-title":"Social big data: recent achievements and new challenges","volume":"28","year":"2016","journal-title":"Information Fusion"},{"issue":"4","key":"key2025042207255394700_ref004","doi-asserted-by":"publisher","first-page":"742","DOI":"10.1177\/0047287519859705","article-title":"Similarity and consistency in hotel online ratings across platforms","volume":"59","year":"2020","journal-title":"Journal of Travel Research"},{"key":"key2025042207255394700_ref005","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1016\/j.dss.2013.08.008","article-title":"Understanding the paradigm shift to computational social science in the presence of big data","volume":"63","year":"2014","journal-title":"Decision Support Systems"},{"issue":"2","key":"key2025042207255394700_ref006","first-page":"117","article-title":"Social media analytics: extracting and visualizing Hilton hotel ratings and reviews from TripAdvisor","volume":"34","year":"2014","journal-title":"International Journal of Information Management"},{"issue":"3","key":"key2025042207255394700_ref007","doi-asserted-by":"publisher","first-page":"564","DOI":"10.1108\/intr-05-2017-0212","article-title":"Analyzing key influences of tourists\u2019 acceptance of online reviews in travel decisions","volume":"28","year":"2018","journal-title":"Internet Research"},{"issue":"5","key":"key2025042207255394700_ref008","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1016\/j.im.2018.01.003","article-title":"The role of social media in enhancing guanxi and perceived effectiveness of E-commerce institutional mechanisms in online marketplace","volume":"55","year":"2018","journal-title":"Information and Management"},{"key":"key2025042207255394700_ref009","doi-asserted-by":"crossref","unstructured":"Curry, E. 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