Ananya Sen

Assistant Professor Carnegie Mellon University

  • Pittsburgh PA

Ananya Sen's research interests centre around platforms with a special focus on the media, innovation and more broadly the digital economy.

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Carnegie Mellon University

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Biography

Ananya's research interests centre around platforms with a special focus on the media, innovation and more broadly the digital economy. He uses a variety of empirical techniques to analyze data from field experiments as well as observational data to gain insight into broad research questions. Before moving to Carnegie Mellon, he was a Post Doctoral Associate at MIT Sloan School of Management. He received a Ph.D in Economics from the Toulouse School of Economics.

Areas of Expertise

Digital Economics
Media
Digitization
Platforms
Education

Media Appearances

Banned books often get circulation bump, new study finds

Axios  online

2023-10-30

What they're saying: "The primary goal of book bans is to restrict access to books, but conversations about the bans often garner attention on a wider scale," study co-author Ananya Sen said.

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Companies accidentally fund online misinformation via ads

Futurity  online

2024-06-18

“Online misinformation can have significant consequences, including sowing political discord and exacerbating the climate crisis,” notes Ananya Sen, assistant professor of information systems and economics at Carnegie Mellon’s Heinz College, who coauthored the study.

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Social

Accomplishments

Management Science Meritorious Service Award

2022

INFORMS ISS Gordon Davis Young Scholar Award

2022

Management Science Distinguished Service Award

2023

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Education

Delhi University

B.A.(Hons)

Economics

2008

Cambridge University

B.A.(Hons)

Economics

2010

Toulouse School of Economics

Ph.D

Economics

2016

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Articles

Antiracist Curriculum and Digital Platforms: Evidence from Black Lives Matter

Management Science

2022

In this paper, we examine the impact of racially charged events on the demand for antiracist classroom resources in U.S. public schools. We use book requests made by teachers on DonorsChoose, the largest crowdfunding platform for public school teachers, as a measure of intent to address race-related topics in the classroom. We use the precise timing of high-profile police brutality and other racially charged events in the United States (2010–2020) to identify their effect on antiracism requests relative to a control group. We find a significant increase in antiracism requests following the killing of George Floyd in 2020 and a null effect for all other events in the decade. We also find an increase in requests for books featuring Latinx, Asian, Muslim, and Jewish cultures, suggesting that a focus on equality for one group can spill over and yield culturally aware dialogues for other groups as well. Event studies suggest that local protests played a role in motivating some of the teachers to post these requests. In just four months following George Floyd’s death, $3.4 million worth of books featuring authors and characters from marginalized communities were successfully funded, reaching more than half a million students. Text analysis of impact notes posted by teachers suggests that hundreds of thousands of young students are being engaged in discussions about positive affirmation and cross-cultural acceptance.

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Climate Change Framing and Innovator Attention: Evidence from an Email Field Experiment

Proceedings of the National Academy of Sciences

2023

Drawing the attention of innovators to climate change is important for green innovation. We report an email field experiment with MIT using messages about the impact of climate change to invite innovators (SBIR grantees) to apply to a technology competition. We vary our messages on the time-frame and scale of the human cost of climate change across scientifically valid scenarios. Innovator attention (clicks) is sensitive to climate change messaging. These changes in clicks also predict higher application rates. The response varies by individual characteristics such as location-based exposure to climate change risks and whether innovators have climate-related innovations. Finally, using a structural model of innovator attention, we provide estimates of the implied discount rate of time and the elasticity of attention to lives at stake.

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The Editor and the Algorithm: Recommendation Technology in Online News

Management Science

2024

We run a field experiment to study the relative performance of human curation and automated personalized recommendation technology in the context of online news. We build a simple theoretical model that captures the relative efficacy of personalized algorithmic recommendations and curation based on human expertise. We highlight a critical tension between detailed, yet potentially narrow, information available to the algorithm versus broad (often private), but not scalable, information available to the human editor. Empirically, we show that, on average, algorithmic recommendations can outperform human curation with respect to clicks, but there is significant heterogeneity in this treatment effect. The human editor performs relatively better in the absence of sufficient personal data and when there is greater variation in preferences. These results suggest that reverting to human curation can mitigate the drawbacks of personalized algorithmic recommendations. Our computations show that the optimal combination of human curation and automated recommendation technology can lead to an increase of up to 13% in clicks. In absolute terms, we provide thresholds for when the estimated gains are larger than our estimate of implementation costs.

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