(사)국제융복합연구원

키워드

초록

This study aims to analyze the impact of social media recommendation
algorithms' biases on the spread of fake news and explore countermeasures. Through a
literature review, the relationship between algorithmic bias and fake news dissemination
is examined, and case studies of major social media platforms' recommendation
algorithms are analyzed to identify the mechanisms of bias occurrence and real-world
examples. The results show that the biases in social media algorithms lead to echo
chamber effects, accelerate the spread of fake news, and exacerbate political polarization
and social conflicts. In response, technical, institutional, and social approaches are
proposed. This study is expected to raise awareness about the issues of algorithmic bias
and fake news and contribute to seeking countermeasures through collaboration among
various sectors of society.

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