Abstract
1- Introduction
2- Related work
3- Methodology
4- Case study
5- Discussion and implications
6- Conclusions
Acknowledgement
References
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).