Gianmarco De Francisci Morales

@gdfm.bsky.social

Principal Researcher & Team Lead @CENTAI. Formerly @ISI_Foundation, @QCRI, @Aalto, @YahooResearch. Scalable data mining & computational social science. https://gdfm.me/research

This is a good way to think about AI’s shortfall. It’s the journey that brings satisfaction more than the destination. The AI shortcut omits the struggle/friction/elation that makes the outcome worthwhile. Weirdly, it’s also why billionaires become assholes—no friction, no joy.

Dr. Sarah Parcak @indyfromspace.bsky.social · 2mo ago

I finally figured out why AI causes such a visceral reaction in thinking humans: I am writing my book chapter on PLAY, and AI is the opposite of play. We play for the joy of the process, not for the outcome. Yes it is nice to win, to have the art/ poem, but the point of life is to play.

Zohran Mamdani said he's going to start taxing rich people who buy luxury housing in NYC but don't actually live in there, and the former CEO of Twitter/X called it "actually one of the scariest things I have ever seen."

Linda Yaccarino replies to a Zohran Mamdani tweet to say that taxing rich people's penthouses is "actually one of the scariest things I have ever seen"

📣 Manuscript out! 📣 Do you struggle in navigating the maze of ABM methods? 🧭 This works unifies the literature on ABM calibration/estimation within a single comprehensive taxonomy: 🎲 sampling-based methods 🤖 meta-models 📖 open-box methods with @gdfm.bsky.social 💡 papers.ssrn.com/sol3/papers....

Estimating Parameters of Agent-Based Models from Data: A Methodological Review

Calibrating Agent-Based Models (ABMs) is essential for grounding their simulated dynamics in empirical reality, yet parameter estimation, a core part of calibra

papers.ssrn.com

New paper in Science: In a platform-independent field experiment, we show that reranking content expressing antidemocratic attitudes and partisan animosity in social media feeds alters affective polarization. 🧵

Today, social media platforms hold the sole power to study the effects of feed-ranking algorithms. We developed a platform-independent method that reranks participants’ feeds in real time and used this method to conduct a preregistered 10-day field experiment with 1256 participants on X during the 2024 US presidential campaign. Our experiment used a large language model to rerank posts that expressed antidemocratic attitudes and partisan animosity (AAPA). Decreasing or increasing AAPA exposure shifted out-party partisan animosity by more than 2 points on a 100-point feeling thermometer, with no detectable differences across party lines, providing causal evidence that exposure to AAPA content alters affective polarization. This work establishes a method to study feed algorithms without requiring platform cooperation, enabling independent evaluation of ranking interventions in naturalistic settings.

While limited to one ABM, this work fills a critical gap in the ABM calibration literature, providing the first structured comparison of DA and LBI for latent state inference. Kudos to Marco, Corrado, and Gianmarco for such a wonderful collaboration! Hope you enjoy it 👉 arxiv.org/abs/2509.17625

Comparing Data Assimilation and Likelihood-Based Inference on Latent State Estimation in Agent-Based Models

In this paper, we present the first systematic comparison of Data Assimilation (DA) and Likelihood-Based Inference (LBI) in the context of Agent-Based Models (ABMs). These models generate observable t...

arxiv.org

Almost back from #ic2s2 (thanks Lufthansa). The most positively-surprising impression from the conference, almost a decade after the first edition, is how much the discipline has coalesced. In 2016, it was easy to distinguish a paper authored by computer scientists vs sociologists. Not so easy now!

🚨Are moral judgements biased by the gender of the subject? We find *no* direct effect when looking at Reddit! Our causal study design is based on carefully matching similar situations that people with different genders experience (and share). Study led by @loreb92.bsky.social rdcu.be/eumlQ

Moral judgments in online discourse are not biased by gender

Scientific Reports - Moral judgments in online discourse are not biased by gender

rdcu.be