Aarushi Kalra
Postodoctoral Prize Research Fellow at Nuffield and Economics, Oxford || Digital Economies/ Development/ Political Economy || Cofounder Bahujan Economists || aarushirita.github.io
- new yorkers cant not vote for the guy explaining rank choice voting in hindi/urdu 😪
- 🚀 Calling all Master's & PhD students abroad! Join our Admission Abroad Mentorship Program (AAMP) as a mentor. Guide mentees through applications, review materials & provide support. Give back & help shape future Bahujan scholars! Form link: forms.gle/LUfET2Stzv2a... #Gradschool
- Reposted by Aarushi KalraIn case somebody missed this yesterday, while watching a political car-crash unfold: "The Means of Prediction - How AI Really Works (and Who Benefits)" is now in the UChicago Press catalog, and available for pre-order online! press.uchicago.edu/ucp/books/bo...
- Reposted by Aarushi KalraThe WS on 𝗧𝗵𝗲 𝗘𝗰𝗼𝗻𝗼𝗺𝗶𝗰𝘀 𝗼𝗳 𝗗𝗶𝗴𝗶𝘁𝗶𝘇𝗮𝘁𝗶𝗼𝗻 - jointly held w/ UCLouvain, LCII,Telecom Paris, TSE, Uni Warsaw - just wrapped up. Congratulations to @chidiya.bsky.social & @juliusgoedde.bsky.social - both won the Best Paper(s) Award 👏 🙏 to the local organizers @tse-fr.eu ℹ️ www.digital-economics.org
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- And so it begins 😞... www.bbc.com/news/article...
- Is the pattern in TikTok blackouts... Ugh... Random?
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- Reposted by Aarushi KalraThis article should be required reading for anyone commenting on the political effects of social media.
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- Reposted by Aarushi Kalra"you'll be visited by three spirits" The three spirits
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- could not have written this post better myself: really appreciate it, @rajivsethi.bsky.social! As correctly pointed out, the hard question is whether diversification provides a way to moderate without censoring: the model-based counterfactuals show that partial diversification could be the answer.
- throwing random content at users helps algorithms learn user preferences while retaining users. In related work, I try to think of other viewpoint-blind policy measures to "nudge" the supply of hate to reduce exposure: inserting apolitical local news about devo issues aarushirita.github.io/papers/
- Reposted by Aarushi KalraInteresting experimental paper on online hate by @chidiya.bsky.social treatment group gets randomized feed instead of algo-curated, exposure to toxic content (TC) drops, engagement drops, search for TC rises, sharing of TC rises relative to exposure: www.econthatmatters.com/2024/11/can-...
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- Thrilled to share that my work on feed-ranking algorithms, based on a large-scale experiment I conducted with 5 million people in India, was recently featured on the Economics that really matters blog! So excited for feedback from folks in this lovely space 🦚 www.econthatmatters.com/2024/11/can-...
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- Reposted by Aarushi KalraThe composition of a lot of the economics starter packs alone on here was revelatory on the nature of 'homophily in citation patterns and racial clusters in networks'...We can definitely do better as a field #Econsky
- Papers authored by Black, Hispanic or Asian economists receive 5.1% to 9.6% fewer citations than those by White scholars. The citation gap is largely driven by homophily in citation patterns and racial clusters in networks (i.e., cite authors from own racial group). www.nber.org/papers/w33150
- "By allowing people to mute content in fine-tuned and personalized ways, it reduces the incentive to mute people." A very important insight! Would depend on whether the "Discover" algorithm is content based, in which case we still end up in very segregated echo-chambers. <shameless plug for JMP>
