نژاد پرستی در بازبینی های گردشگری و توریسم
ترجمه نشده

نژاد پرستی در بازبینی های گردشگری و توریسم

عنوان فارسی مقاله: نژاد پرستی در بازبینی های گردشگری و توریسم
عنوان انگلیسی مقاله: Racism in tourism reviews
مجله/کنفرانس: مدیریت توریسم – Tourism Management
رشته های تحصیلی مرتبط: گردشگری توریسم و جهانگردی، حقوق
گرایش های تحصیلی مرتبط: مدیریت گردشگری، حقوق بین الملل
کلمات کلیدی فارسی: توریسم، نژاد پرستی، پردازش متن بازبینی، عقیده کاوی
کلمات کلیدی انگلیسی: Tourism, Racism, Review text processing, Sentiment analysis
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.tourman.2020.104100
دانشگاه: Deakin University, Geelong, Australia
صفحات مقاله انگلیسی: 18
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2020
ایمپکت فاکتور: 9.657 در سال 2019
شاخص H_index: 179 در سال 2020
شاخص SJR: 3.068 در سال 2019
شناسه ISSN: 0261-5177
شاخص Quartile (چارک): Q1 در سال 2019
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E15114
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

1- Introduction

2- Related work

3- Methodology

4- Case study

5- Discussion and implications

6- Conclusions

Acknowledgement

References

بخشی از مقاله (انگلیسی)

Abstract

Racism is increasingly recognised as a key driver of unfair inequalities in power, resources and opportunities across racial groups. A comprehensive understanding of racism is beneficial to activist groups, policymakers and governments. Traditional approaches, such as surveys and interviews, are usually time-consuming and inefficient in capturing the occurrence of large-scale racism. In this study, we utilise routinely collected data available on tourism websites to assess self-reported racism in the tourism domain. We present a data acquisition procedure that collects racism-related reviews from the Internet at the global scale and then utilise statistics and natural language processing techniques to analyse and explore racism in terms of its tendency, distribution, semantics and characteristics. The effectiveness of the proposed method is demonstrated in a case study, in which we acquire racism-related data at the global scale and validate the impact of racial discrimination on tourists’ experience.

Introduction

Racism is a social phenomenon that should not be ignored. It is a key factor that leads to unfair and avoidable inequalities in power, resources and opportunities across racial or ethnic groups (Berman & Paradies, 2010). This claim is reflected not only by increasing political attention but also by growing media coverage (Rodrigues, Niemann, & Paradies, 2019). Racism has various manifestations. Thus, it has been studied as a concept (i.e. beliefs, ideologies or worldviews) and as an action (i.e. forms of racial discrimination, such as offensive language or racist practices) (Paradies, 2016; Priest & Williams, 2017). Racism research is inherently multidisciplinary and has been the focus of research in humanities (Levy, 2017), social sciences (Henricks, 2015), cultural studies (Seikkula, 2019), economics (Lane, 2016), and law (Hirsh & Cha, 2018), among others. With the development of the Internet, especially the rise of social networks, assumed anonymity and digital freedom of speech encourage people to freely disclose their racist ideologies or adopt an aggressive online behaviour with limited consequences. In today’s digital era, racism has become common and virulent on the Internet. It has also drawn much research attention in various fields, from engineering and technical science to psychology and social sciences (Jakubowicz et al., 2017; Bliuc, Faulkner, & Jakubowicz, 2018; Fortuna & Nunes, 2018).