As effect of big data and artificial intelligence, algorithmic risk has attracted attention of scholars. This study synthesises research on algorithmic risk and identifies hotpots and trends using visualization analysis. We retrieved research articles (2013 to 2023) from the Web of Science with topic research. Bibliometric analysis shows that since 2017, articles related to algorithmic risk have increased rapidly, most research papers on algorithmic risk published in law, management, business, and other outlets. The literature analysis reveals that the core research themes include hazard factor, algorithmic risks of new technologies, governance and regulation methods. Social media and the framework of governance are identified as the two emerging trends in the domain. Based on these findings, this paper proposes that more attention should be paid to the algorithmic risk governance of platform enterprises and algorithmic administration in the future. This paper presents a visual, quantitative and large-scale review of the most recent literature on algorithmic risk research, providing ideas to the way forward for researchers and a system thinking for practitioners.
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Visualization Analysis of Algorithmic Risk Research Based on CiteSpace
Semantic Scholar · 2024
Abstract
As effect of big data and artificial intelligence, algorithmic risk has attracted attention of scholars. This study synthesises research on algorithmic risk and identifies hotpots and trends using visualization analysis. We retrieved research articles (2013 to 2023) from the Web of Science with topic research. Bibliometric analysis shows that since 2017, articles related to algorithmic risk have increased rapidly, most research papers on algorithmic risk published in law, management, business, and other outlets. The literature analysis reveals that the core research themes include hazard factor, algorithmic risks of new technologies, governance and regulation methods. Social media and the framework of governance are identified as the two emerging trends in the domain. Based on these findings, this paper proposes that more attention should be paid to the algorithmic risk governance of platform enterprises and algorithmic administration in the future. This paper presents a visual, quantitative and large-scale review of the most recent literature on algorithmic risk research, providing ideas to the way forward for researchers and a system thinking for practitioners.