مقاله انگلیسی کاربران Airbnb به چه چیزی اهمیت میدهند؟ تجزیه و تحلیل نظرات نظر آنلاین
04 شهریور 1397 | 09:29
عنوان فارسی مقاله: کاربران Airbnb به چه چیزی اهمیت میدهند؟ تجزیه و تحلیل نظرات نظر آنلاین
عنوان انگلیسی مقاله: What do Airbnb users care about? An analysis of online review comments
مجله/کنفرانس: International Journal of Hospitality Management
رشته های تحصیلی مرتبط: مدیریت
گرایش های تحصیلی مرتبط: مدیریت بازرگانی، بازاریابی
نوع نگارش مقاله: پژوهشی - research
نمایه: scopus - master journals - JCR
DOI: doi.org/10.1016/j.ijhm.2018.04.004
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنالی
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور(IF): 3.455(2017)
شاخص H_index: 82
SJR: 2.027
شناسه ISSN: 02784319
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 13
کد محصول: EN6
فهرست انگلیسی مطالب
Abstract
Keywords
Introduction
Literature review
Research design
Findings
Discussion and implications
Acknowledgement
Appendix A
References
Keywords
Introduction
Literature review
Research design
Findings
Discussion and implications
Acknowledgement
Appendix A
References
نمونه متن انگلیسی
Abstract
This study investigates the attributes that influence Airbnb users’ experiences by analysing a “big data” set of online review comments through the process of text mining and sentiment analysis. Findings reveal that Airbnb users tend to evaluate their experience based on a frame of reference derived from past hotel stays. Three key attributes identified in the data include ‘location’, ‘amenities’ and ‘host’. Surprisingly, ‘price’ is not identified as a key influencer. The analysis suggests a positivity bias in Airbnb users’ comments while negative sentiments are mostly caused by ‘noise’. This research offers an alternative approach and more coherent understanding of the Airbnb experience. Methodologically, it contributes by illustrating how big data can be used and visually interpreted in tourism and hospitality studies.
This study investigates the attributes that influence Airbnb users’ experiences by analysing a “big data” set of online review comments through the process of text mining and sentiment analysis. Findings reveal that Airbnb users tend to evaluate their experience based on a frame of reference derived from past hotel stays. Three key attributes identified in the data include ‘location’, ‘amenities’ and ‘host’. Surprisingly, ‘price’ is not identified as a key influencer. The analysis suggests a positivity bias in Airbnb users’ comments while negative sentiments are mostly caused by ‘noise’. This research offers an alternative approach and more coherent understanding of the Airbnb experience. Methodologically, it contributes by illustrating how big data can be used and visually interpreted in tourism and hospitality studies.
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