Exploring nexus of social media algorithms, content creators, and gender bias: a systematic literature review - Lou, Shijun; Adzharuddin, Nor Azura; Syed Zainudin, Sharifah Sofiah; Omar, Siti Zobidah (Asian Scholars Network, 2024)
Abstract: Drawing on the PRISMA framework, this study systematically investigates the dynamics between social media algorithms, content creators, and gender bias. An analysis of 18 quantitative and mixed-method studies from the Web of Science and Scopus databases, spanning 2019 to 2023, uncovers three main research trajectories: algorithms' influence on gender bias, their role in shaping content, and the interactions between algorithms, gender bias, and content creators. The review synthesizes diverse theoretical approaches and models, offering comprehensive insights into the complex nexus of algorithms, gender bias, and content creators. The application of varied research methodologies, including experiments, surveys, and content analyses, facilitates a thorough examination of algorithmic impacts. The chosen studies, focusing on different social media platforms and algorithmic features, reflect the varied interests of researchers. The findings reveal that algorithms perpetuate gender stereotypes by processing and learning content imbued with gender biases and further marginalizing gender minorities, reinforcing binary gender norms. The algorithmic curation of popular content also introduces inequities among content creators. Highlighting the need for equitable and inclusive digital environments, this review advocates for ethical content creation and algorithmic practices to mitigate gender bias and foster equality on social media platforms.