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Momin M. Malik is a multidisciplinary researcher who brings statistical modeling to bear on critical, reflexive questions with and about large-scale digital trace data. He is broadly concerned with issues of algorithmic power and control, and of validity and rigor in computational social science. In addition to empirical work modeling social media and mobile phone sensor data, he works on how to understand statistics, machine learning, and data science from critical and constructivist perspectives, on ethical and policy implications of predictive modeling, and on understanding and communicating foundational problems in statistical models of social networks. He has an undergraduate degree in history of science from Harvard, a master's from the Oxford Internet Institute, and a PhD from Carnegie Mellon University's School of Computer Science.


Oct 18, 2013

The Challenges of Defining 'News Literacy'

This brief seeks to stimulate a discussion among the grantees about different approaches to defining, framing, and understanding core concepts such as 'news' and 'news literacy',… More

Feb 23, 2012

Youth and Digital Media: From Credibility to Information Quality

Building upon a process- and context-oriented information quality framework, this paper seeks to map and explore what we know about the ways in which young users of age 18 and… More


Dec 14, 2018

Get to Know Berkman Klein Fellow Momin Malik

a spotlight on one of our 2018-2019 BKC Fellows

Momin is bringing network analysis techniques, various statistical models, topic models, and natural language processing to reduce data in ways that are comprehensive,… More



Can algorithms themselves be biased?

The short answer is, “yes, but it doesn’t really matter when compared to the choice to use machine learning.”

Apr 24, 2019