This study discusses the digital hate speech against refugees during the COVID-19 pandemic. The perspective provided by the ideological dimension of big data was considered in the research process and results were obtained by adopting an innovative approach. Comments, which were written by users to the YouTube videos about COVID-19 and refugees shared by international news organisations, were collected. As a result of the analysis process, it was found that 29 percent of comments contain hate speech. Even though the amount of hate speech is percentually low, they received 49 percent of the likes. The hate speech stated against refugees in the past and during the COVID-19 pandemic have similar patterns. Comments that contain hate speech were categorized as follows: Privilege of Destination Country (50 percent), Purpose-Oriented Hate Speech (13 percent), Hate Speech About Individual Choices and Personal Characteristics (17 percent) and Other (20 percent). Comments classified under Privilege of Destination Country received 62 percent of total likes of hate speech comments. On the other hand, average like count of Privilege of Destination Country and average like count of Purpose-Oriented Hate Speech categories are higher than the general average. Within the scope of the study, linguistic reflection of comments that contain hate speech were visualized with a network map.
: 24 Kasım 2020
|APA||Kuş, O . (2021). Kovid-19 Salgını ve Mültecilere Yönelik Dijital Nefret Söylemi: Büyük Veri Perspektifinden Metin Madenciliği Tekniği ile Kullanıcı Kaynaklı İçeriklerin Analizi . TRT Akademi , 6 (11) , 106-131 . DOI: 10.37679/trta.830736|