This paper aims to clarify how, and what kind of threat was emphasized by the major Arabic newspapers regarding the refugee crisis in 2015. To address this research focus, I conducted a quantitative text analysis on three levels utilizing 59,423 articles from three Pan-Arab newspapers. The first level was scaling the threat level with Latent Semantic Scaling (a semi-supervised machine learning model); second, classifying threat issues with dictionary analysis; and third, identifying the geographical intensity of each article with Newsmap. Finally, I performed a regression analysis with the combined data to reveal their interrelation. I found that threat framing could differ based on the newspaper, refugee status, timing, issue of the article, and geographical factors. Furthermore, the threat level continued to rise over time and reached the highest point during the crisis period. The Pan-Arab newspapers tended to emphasize threats associated with terrorism and crime, rather than social issues, such as housing, labor, and culture. It was also revealed that when geographical variables were added to the analysis, the newspaper articles were more likely to perceive refugees as a cultural threat if they were predominately associated with the Middle East.
|Journal||Journal of Population and Social Studies|
|Publication status||Published - 2020|
All Science Journal Classification (ASJC) codes
- Health(social science)
- Geography, Planning and Development
- Sociology and Political Science
- Social Sciences (miscellaneous)