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Ittefaq et al. (2024)
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High(4)High quality. Established institution or organization with editorial oversight and accountability.
Rating inherited from publication venue: ScienceDirect
Empirical study analyzing media framing of AI across Global North and South newspapers (2010-2023), revealing disparities in AI coverage that inform public understanding and policy discourse around artificial intelligence.
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journal articleanalysis
Summary
A comprehensive analysis of AI news coverage in 12 newspapers from 2010-2023 using topic modeling and sentiment analysis. The study reveals differences in AI framing between Global North and South media outlets.
Key Points
- •Analyzed AI news coverage across 12 countries from 2010-2023 using advanced text analysis techniques
- •Identified nine major frames of AI coverage, with business and economic impacts being most prevalent
- •Revealed significant differences in AI framing between Global North and South media outlets
Review
This study provides a comprehensive examination of how artificial intelligence is portrayed in news media across 12 countries, bridging a significant research gap in understanding global media representations of AI. Using Latent Dirichlet Allocation (LDA) topic modeling and sentiment analysis, the researchers analyzed 38,787 news articles to identify prevalent frames and sentiment tones in AI coverage. The research reveals critical insights into how different regions frame AI, with Global North newspapers giving lower coverage to AI solutions and healthcare applications, while Global South media emphasized economic cooperation. The sentiment analysis showed a predominantly neutral tone (65.63%), with 21.04% negative and 13.33% positive headlines. Notably, newspapers like The Guardian and The New York Times tended to frame AI more negatively, while China Daily and Bangkok Post presented more positive perspectives. This study contributes significantly to understanding how media framing shapes public perception of AI and highlights the divergent narratives emerging from different global contexts.
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