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Leisure Tourism

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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...

Author(s)
Xiang Zheng; Du QianZhou; Ma YuFeng; Fan WeiGuo
Publisher
Elsevier Ltd, Oxford, UK
Citation
Tourism Management, 2017, 58, pp 51-65
Abstract

As an emerging research paradigm, big data analytics has been gaining currency in various fields. However, in existing hospitality and tourism literature there is scarcity of discussions on the quality of data which may impact the validity and generalizability of research findings. This study...

Author(s)
Xiang Zheng; Du QianZhou; Ma YuFeng; Fan WeiGuo
Publisher
Springer Berlin, Heidelberg, Germany
Citation
Information Technology and Tourism, 2018, 18, 1/4, pp 43-59
Abstract

Online reviews have been extensively studied in the hospitality and tourism literature. However, while user-provided photos embedded in online reviews accumulate in large quantities, their informational value has not been well understood likely due to technical challenges. The goal of this study is ...

Author(s)
Ma YuFeng; Xiang Zheng; Du QianZhou; Fan WeiGuo
Publisher
Elsevier Ltd, Amsterdam, Netherlands
Citation
International Journal of Hospitality Management, 2018, 71, pp 120-131
Abstract

Following the idiom "A picture is worth a thousand words", recent tourism and hospitality research has adopted deep learning techniques to better understand the content and effect of photographs. This exploratory study delves into image content, to learn which sets of images relate to positive and...

Author(s)
Zach, F. J.; Ma YuFeng; Fox, E. A.
Publisher
Texas A & M University Press, College Station, USA
Citation
e-Review of Tourism Research, 2019, 16, 2/3, pp 156-164