基本信息
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职业迁徙
个人简介
I investigate computational methods to discover socially-beneficial knowledge from text and social networks. Examples include tracking diseases, measuring effectiveness of public health campaigns, informing crisis response, preventing online harassment, detecting deceptive marketing, and identifying unsafe products.
The methods rely on machine learning, natural language processing, and social network analysis. Areas of technical contribution include domain adaptation, learning from label proportions, and causal inference.
The methods rely on machine learning, natural language processing, and social network analysis. Areas of technical contribution include domain adaptation, learning from label proportions, and causal inference.
研究兴趣
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WWW 2023pp.2808-2818, (2023)
SN Comput. Sci.no. 5 (2023): 1-12
Social Science Research Network (2023)
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COMPANION OF THE WORLD WIDE WEB CONFERENCE, WWW 2023pp.1020-1029, (2023)
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international conference on weblogs and social mediano. 2 (2021): 19-22
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