Keller Jordan on Twitter / X

Social media promotion improves job market outcomes

Social media has transformed how academics disseminate research, but its effect on academic job outcomes remains unclear. Previous research has shown correlations between social media exposure and metrics like citation counts, but these relationships may be confounded by unobserved factors such as researcher quality or access to professional networks. We examine whether social media promotion causally affects job market outcomes in economics through a field experiment on Twitter (now X). We first collect tweets about job market papers from 519 candidates and post them from a dedicated account. We then randomize half of the posts to be quote-tweeted by established economists in the candidates’ fields, and measure the effects on both online visibility and hiring outcomes. We find that posts in the treatment group receive 441% more views and 303% more likes than those in the control group. Candidates whose posts were assigned to be quote-tweeted receive one additional flyout invitation compared to the control group average of 5.4 flyouts. Furthermore, women in the treatment group receive 0.9 more job offers than women in the control group, who receive 3 offers on average. Exploring mechanisms, we find that academic reputation drives these results, with stronger effects for quote-tweets from highly cited scholars and for candidates from top institutions. Our findings suggest social media promotion causally increases research visibility and improves academic job market outcomes.

David Rozado on Twitter / X

1. Have we been measuring AI political bias wrong? In a new paper @PTetlock and I argue that we might have. Studies have found that AIs tend to produce left-of-center responses to politically loaded questions. But ideological preferences are not the same as epistemic failure. pic.twitter.com/JuGrboRVb0— David Rozado (@DavidRozado) June 22, 2026

Deb Raji on Twitter / X

Almost exactly three years ago, in 2023, @alondra gave the keynote @FAccTConference, literally titled "Thick Alignment".This has been so far from a "niche" view! https://t.co/0db7qcM6LB pic.twitter.com/z5FqDz8TUv— Deb Raji (@rajiinio) August 22, 2026

Cas (Stephen Casper) on Twitter / X

It is hard to overstate how disappointing I think this new paper from Oxford, OpenAI, Anthropic, and Google (et al) is. I can't take it seriously as academic work, just as propaganda. It also has some very bad scholarship and questionable adherence to research ethics. Having… pic.twitter.com/Z5fBx360ya— Cas (Stephen Casper) (@StephenLCasper) May 13, 2026

Weights & Biases on Twitter / X

Hey MCP developers!Let’s talk about something broken 🧠🛠️Agents are calling tools left and right.But what happens inside those tools?No traces. No visibility. No security.Just a black box. 🕋The observability gap is real. Let's fix it together with observable[.]tools pic.twitter.com/htHmtBaJGH— Weights & Biases (@wandb) April 9, 2025

Lei Yang on Twitter / X

Got burned by an Apple ICLR paper — it was withdrawn after my Public Comment.So here’s what happened. Earlier this month, a colleague shared an Apple paper on arXiv with me — it was also under review for ICLR 2026.The benchmark they proposed was perfectly aligned with a… pic.twitter.com/ON782SFNjI— Lei Yang (@diyerxx) November 27, 2025

Communication Bias in Large Language Models: A Regulatory Perspective

Large language models (LLMs) are increasingly central to many applications, raising concerns about bias, fairness, and regulatory compliance. This paper reviews risks of biased outputs and their...

Laura Luebbert, PhD on Twitter / X

MVS has dismissed our findings as "typographical errors and minor oversights," accused Lior and me of being "unprofessional," and called any allegations "totally bizarre." For context, I am showing four examples of duplicated data as described in our arxiv manuscript (Fig 3 & 4). pic.twitter.com/ZuTX6ivBGM— Laura Luebbert, PhD (@NeuroLuebbert) July 11, 2024

Distributional Training Data Attribution: What do Influence Functions Sample?

Randomness is an unavoidable part of training deep learning models, yet something that traditional training data attribution algorithms fail to rigorously account for. They ignore the fact that, due to stochasticity in the initialisation and batching, training on the same dataset can yield different models. In this paper, we address this shortcoming through introducing _distributional_ training data attribution (d-TDA), the goal of which is to predict how the distribution of model outputs (over training runs) depends upon the dataset. Intriguingly, we find that _influence functions_ (IFs), a popular data attribution tool, are 'secretly distributional': they emerge from our framework as the limit to unrolled differentiation, without requiring restrictive convexity assumptions. This provides a new perspective on the effectiveness of IFs in deep learning. We demonstrate the practical utility of d-TDA in experiments, including improving data pruning for vision transformers and identifying influential examples with diffusion models.

Do Science <i>Kardashians</i> Get Citation Premium? Self‐Fulfilling Effects of Social Media on Scientific Impact

ABSTRACT We analyze whether the visibility of scientists on social media affects the number of academic citations. We use the global COVID‐19 pandemic as a quasinatural experiment that exogenously increased public attention and the demand for expertise. Using publications on COVID‐related topics by social media stars and their coauthors prior to the outbreak of the pandemic, we find that social media stars' pre‐COVID‐era papers received about – more citations annually per paper after 2019. Quantitatively comparable results are obtained when we use scientists' Kardashian index (K‐index) as a benchmark for stardom, however we find no significant effects when using the intensive margin of scientists' K‐indexes. We provide a brief discussion of policy implications in light of these findings.

Elena Rossini 🌈 (@_elena@mastodon.social)

Attached: 2 images Dear Fedi friends, Apologies for another toot about #WSocial but I am genuinely shaking right now. The @EUCommission@ec.social-network.europa.eu and its president Ursula von der Leyen have recently migrated their ATproto (Bluesky) accounts to W Social. I cannot fathom why they would pick a private enterprise whose leaders didn't even have ATproto accounts 3 months ago... and who are so open to having their users' data mined to train European AI models. My articles on them: 🔗 : https://blog.elenarossini.com/tag/w-social/ Wow. Just wow.

Elena Rossini 🌈 (@_elena@mastodon.social)

🚨 New post alert 📝 A deep dive into #WSocial with some fascinating findings: candid statements about their motives, a Greta Thunberg connection, potential AI plans (!!!) Why write about it again? I still had so many questions after publishing my first article. I spent 3 weeks watching every interview I could find and connecting the dots. I hope you'll enjoy this piece: 🔗 : https://blog.elenarossini.com/the-untold-story-about-w-social-unconventional-beginnings-strategic-pitches-conflicting-signals/ #blog #longread #privacy #DataMining #Europe

👋 Jan on Twitter / X

Introducing Jan-v1: 4B model for web search, an open-source alternative to Perplexity Pro.In our evals, Jan v1 delivers 91% SimpleQA accuracy, slightly outperforming Perplexity Pro while running fully locally.Use cases:- Web search- Deep ResearchBuilt on the new version… pic.twitter.com/YApIShOAHI— 👋 Jan (@jandotai) August 12, 2025

Anton Shekhovtsov on Twitter / X

This is Elon Musk, a techno-oligarch with 241 million followers on TwitterX, spreading and amplifying Ceuta-linked right-wing disinformation, with one message reaching 9.9 million views and the other 7.9 million as of right now.And here's the EU: "The European External Action… pic.twitter.com/590Vm7J5Ob— Anton Shekhovtsov (@A_SHEKH0VTS0V) August 5, 2026

Ali Sina Önder on Twitter / X

Does your social media visibility affect your citations? Yes because social media visibility enhances your "expert" status. Here is the brand new paper with @econ_lessmann and Max Rose: https://t.co/KJaxgOaAYQ @davidstadelmann @MishaTeplitskiy @csugimoto @voxeu @AntonioFatas pic.twitter.com/kioHRJ0gYH— Ali Sina Önder (@asonder79) May 3, 2026