Ananya Sen
Assistant Professor | Carnegie Mellon University
Pittsburgh, PA, UNITED STATES
Ananya Sen's research interests centre around platforms with a special focus on the media, innovation and more broadly the digital economy.
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 (5)
Digital Economics
Media
Digitization
Platforms
Education
Media Appearances (2)
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.
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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Accomplishments (5)
Alfred Blumstein Career Development Professorship (professional)
2024
Andrew Carnegie Fellow, Class of 2024 (professional)
2024
Management Science Distinguished Service Award (professional)
2023
INFORMS ISS Gordon Davis Young Scholar Award (professional)
2022
Management Science Meritorious Service Award (professional)
2022
Education (4)
MIT Sloan School of Management: Post Doctoral Fellow 2019
Toulouse School of Economics: Ph.D, Economics 2016
Cambridge University: B.A.(Hons), Economics 2010
Delhi University: B.A.(Hons), Economics 2008
Links (3)
Articles (5)
The Role of Advertisers and Platforms in Monetizing Misinformation: Descriptive and Experimental Evidence
National Bureau of Economic Research2024 The financial motivation to earn advertising revenue by spreading misinformation has been widely conjectured to be among the main reasons misinformation continues to be prevalent online. Research aimed at reducing the spread of misinformation has so far focused on user-level interventions with little emphasis on how the supply of misinformation can itself be countered. In this work, we show how online misinformation is largely financially sustained via advertising, examine how financing misinformation affects the advertisers and ad platforms involved and outline ways of reducing the financing of misinformation. First, we find that advertising on misinformation outlets is pervasive for companies across several industries and is amplified by digital ad platforms that automatically distribute companies’ ads across the web. Using an information provision survey experiment, we show that people decrease their demand for a company’s products or services upon learning about its role in monetizing misinformation via online ads. To shed light on why misinformation continues to be monetized despite the potential backlash for the advertisers involved, we survey decision-makers at companies. We find that most decision-makers are unaware of their companies’ ads appearing on misinformation websites but have a strong preference to avoid appearing on such websites. Moreover, those uncertain and unaware about their role in financing misinformation increase their demand for a platform-based solution to reduce monetizing misinformation upon learning about how platforms amplify ad placement on misinformation websites. We identify low-cost, scalable information-based interventions that digital platforms could implement to reduce the financial incentive to misinform and counter the supply of misinformation online.
(How) Does User-Generated Content Impact Content Generated by Professionals? Evidence from Local News
Management Science2024 Many platforms host user-generated content (UGC) and content developed by professionals side by side. However, thus far, their impact on platform ecosystems has been mostly studied in isolation. In this paper, we use data from a network of 122 local news outlets hosted by an online news platform to study the spillover effects from UGC developed by citizen journalists to the content developed by professional journalists. We use the removal of a status index associated with citizen journalists as an exogenous shock to their supply of UGC to identify these spillover effects. We find that experienced citizen journalists reduce their production of content when this status index is removed. We then find that inexperienced professional journalists increase their output in response to this behavior. However, as a result of these changes, we find a reduction in the overall content hosted by the platform, especially in the case of local news and in more isolated regions. We further show that this is likely to have detrimental effects for the platform. In particular, there is a decline in overall viewership, and the platform may need to hire and pay salaries to more professional journalists to produce enough articles to close the gap left by the departing citizen journalists. Our work contributes to the literature on UGC and online platforms and to the literature on local news.
The Editor and the Algorithm: Recommendation Technology in Online News
Management Science2024 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.
Climate Change Framing and Innovator Attention: Evidence from an Email Field Experiment
Proceedings of the National Academy of Sciences2023 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.
Antiracist Curriculum and Digital Platforms: Evidence from Black Lives Matter
Management Science2022 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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