Gender-based violence (GBV) against immigrant women living in Canada : blending big data and critical discourse approaches to news media representations

Abstract

Discussions on the role of gender in migration have increased significantly in the last few years. This study explores the impact of gender-based violence (GBV) on immigrant women living in Canada as reported and constructed by news media. The study was carried out using Big Data, with the aid of several clustering and classifying artificial intelligence (AI) technologies (Machine Learning Tools). After a significant amount of news media data was gleaned through such technologies, critical discourse analysis (CDA) was used to examine how discourse, specifically from Canadian news media, reports and thus constructs GBV against immigrant women living in Canada. Through this critical lens, it was concluded that immigrant women were often viewed as passive victims and never as heroes / survivors / or agents in their lives; they were also presented as ‘other' in Canadian society by news media reflecting stereotypical images of them and exoticizing their GBV experiences. Such constructions, in turn, contributed to aggravating and perpetuating their GBV experiences as well as magnifying pre-existing inequalities.