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"Diversity and inequality in social networks"
Abstract: Online social networks often mirror inequality in real-world networks, from historical prejudice, economic or social factors. Such disparities are often picked up and amplified by algorithms that leverage social data for the purpose of providing recommendations, diffusing information, or forming groups. In this talk, Stoica discusses an overview of my research involving explanations for algorithmic bias in social networks, briefly describing my work in information diffusion, grouping, and general definitions of inequality. Using network models that reproduce inequality seen in online networks, we'll characterize the relationship between pre-existing bias and algorithms in creating inequality, discussing different algorithmic solutions for mitigating bias.
About the speaker: Ana-Andreea Stoica is a doctoral candidate at Columbia University. Her work focuses on mathematical models, data analysis, and inequality in social networks. From recommendation algorithms to the way information spreads in networks, Stoica is particularly interested in studying the effect of algorithms on people's sense of community and access to information and opportunities. She strives to integrate tools from mathematical models—from graph theory to opinion dynamics—with sociology to gain a deeper understanding of the ethics and implications of technology in our everyday lives. Ana grew up in Bucharest, Romania, and moved to the US for college, where she graduated from Princeton in 2016 with a bachelor's degree in Mathematics. Since 2019, she has been co-organizing the Mechanism Design for Social Good initiative.
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