Racism in tourism reviews. (October 2020) - Li, Shu
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. Highlights: Using tourism data to analyse and assess racism at a global scale. An approach is presented to acquire racism-related data and extract information without directly engaging with tourists. Reviews text processing technique is presented to analyse global racism patterns. The method is demonstrated in a case study and the purpose for racism analysis is achieved. A valuable and reliable data source with a large sample size is provided for related research on racism.