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.
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