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个人简介
Broadly, my work investigates a variety of content serving websites such as Search Engines, Online Stores, Job Search Sites or Freelance Marketplaces. In this quickly changing online ecosystem companies track users' every move and feed the collected data into big data algorithms in order to match them with the most interesting, most relevant content. Since these algorithms learn on human data they are likely to pick up on social biases and unintentionally reinforce them. In my PhD work I created a methodology called Algorithmic Auditing which tries to uncover the potential negative impacts of large online systems. Examples of such audits include examining the "Filter Bubble effect" on Google Search, online price discrimination or detecting inequalities in online labor markets.
研究兴趣
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PROCEEDINGS OF 2023 ACM CONFERENCE ON EQUITY AND ACCESS IN ALGORITHMS, MECHANISMS, AND OPTIMIZATION, EAAMO 2023 (2023): 1-14
EWAF (2023)
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arxiv(2023)
Applied Network Scienceno. 1 (2023): 1-29
CoRR (2023)
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Journal of personality and social psychologyno. 4 (2023): 681-698
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