A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism |
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| Affiliation: | 1. Department of Hospitality and Tourism Management, Pamplin College of Business, Virginia Tech, Blacksburg, VA 24061, USA;2. Department of Business Information Technology, Pamplin College of Business, Virginia Tech, Blacksburg, VA 24061, USA;3. Department of Computer Science, Virginia Tech, Blacksburg, VA 24061, USA;4. Center for Business Intelligence & Analytics, Department of Accounting and Information Systems, Pamplin College of Business, Virginia Tech, Blacksburg, VA 24061, USA;1. Natural Resources Recreation and Tourism (NRRT), Warnell School of Forestry and Natural Resources, 180 East Green St., University of Georgia, Athens, GA 30602, USA;2. Department of Hospitality and Tourism Management, 362 Wallace Hall (0429), 295 West Campus Drive, Virginia Tech, Blacksburg, VA, USA;3. Department of Sustainable Biomaterials & Office of International Research, Education, and Development, The International Affairs Offices (IAO), 526 Prices Fork Road (0378), Virginia Tech, Blacksburg, VA 24061, USA;1. School of Management, Harbin Institute of Technology, 150001, China;2. School of Hotel & Tourism Management, The Hong Kong Polytechnic University, Hong Kong;1. Department of Management Studies, IIT Madras, India;2. IIT Madras, India;1. Department of Hospitality and Tourism Management, Pamplin College of Business, Virginia Tech, Blacksburg, VA 24061, USA;2. Department of Hotel, Restaurant & Institutional Management, University of Delaware, Newark, DE 19716, USA;3. Department of Integrated Information Technology, College of Hospitality, Retail, & Sport Management, University of South Carolina, Columbia, SC, USA;1. Department of International Economics and Management, Copenhagen Business School, Porcelænshaven 24B 3.54, DK 2000 Frederiksberg, Denmark;2. Norwegian School of Hotel Management, University of Stavanger, NO 4036 Stavanger, Norway |
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| Abstract: | Online consumer reviews have been studied for various research problems in hospitality and tourism. However, existing studies using review data tend to rely on a single data source and data quality is largely anecdotal. This greatly limits the generalizability and contribution of social media analytics research. Through text analytics this study comparatively examines three major online review platforms, namely TripAdvisor, Expedia, and Yelp, in terms of information quality related to online reviews about the entire hotel population in Manhattan, New York City. The findings show that there are huge discrepancies in the representation of the hotel industry on these platforms. Particularly, online reviews vary considerably in terms of their linguistic characteristics, semantic features, sentiment, rating, usefulness as well as the relationships between these features. This study offers a basis for understanding the methodological challenges and identifies several research directions for social media analytics in hospitality and tourism. |
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| Keywords: | Online reviews Hotel industry Information quality Social media analytics Text analytics Machine learning |
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