Abstract

ABSTRACT For over five decades, researchers explored the volume of coverage countries receive in other countries’ media, the factors that shape countries’ newsworthy, and sentiment in their coverage. However, a quantitative systematic analysis of how countries are covered, specifically, the framing of coverage, has been lacking. We first utilize machine learning for the descriptive inductive identification of frames in large-scale content (N = 105,991 news articles) to examine how US news outlets covered the 55 countries included in the 6th Wave of the World Value Survey, over a year (Study 1). We then examine the factors that predicted the prominence of frames at the country level (Study 2). Study 1 identified three frames—conflict, economic, and human-interest, which correspond with, but also different from, previous framing frameworks. Study 2 found that factors connected to prominence, relatedness, and conflict, predicted the use of specific frames. Prominence (Specifically GDP) increased the use of the economic frame and decreased the conflict one. Relatedness, with emphasis on trade, cultural proximity and geographic distance increased economic framing and decreased conflict framing. Lastly, Conflict-related variables, mainly military expenditure, increased the salience of the conflict frame.

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