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Walter Quattrociocchi @walter4c.bsky.social · 26/11/2025

LLMs don’t form judgments. They skip straight to the answer. No evaluation. No grounding. Just fluent output. When generation bypasses judgment, knowledge becomes a performance. Welcome to Epistemia. PNAS commentary ⬇️ www.pnas.org/doi/10.1073/...

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Reposted by Walter Quattrociocchi

Sander van der Linden @profsanderlinden.bsky.social · 21/11/2025

New study on LLMs shows that while LLMs & humans converge on similar judgments of reliability of news media, they rely on very different underlying processes. In delegating, are we confusing linguistic plausibility with epistemic reliability? The age of "epistemia" www.pnas.org/doi/epdf/10....

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Reposted by Walter Quattrociocchi

Dan Vergano @danvergano.bsky.social · 20/11/2025

How LLMs generate judgments www.nature.com/articles/s43... "driven by lexical and statistical associations rather than deliberative reasoning"

nature.com

How LLMs generate judgments - Nature Computational Science

Nature Computational Science - How LLMs generate judgments

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Reposted by Walter Quattrociocchi

Nature Computational Science @natcomputsci.nature.com · 20/11/2025

📢Research Highlights out today! We highlight work by @walter4c.bsky.social, @matteocinelli.bsky.social, and colleagues on how LLMs generate judgments about reliability and political bias, and how their procedures compare to human evaluation. www.nature.com/articles/s43... #cssky

nature.com

How LLMs generate judgments - Nature Computational Science

Nature Computational Science - How LLMs generate judgments

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Walter Quattrociocchi @walter4c.bsky.social · 18/11/2025

Data changed the info business model: confirmation → echo chambers → infodemics LLMs drop cost of “knowledge-like” content to zero. Result: Epistemia — when language sounds like knowledge. Outsourcing shifts decisions from evidence → plausibility PNAS:https://www.pnas.org/doi/10.1073/pnas.1517441113

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Walter Quattrociocchi @walter4c.bsky.social · 29/10/2025

Grokipedia is not the problem. It’s the signal. What we’re seeing isn’t about AI or neutrality — it’s the rise of the post-epistemic web. The question isn’t: is it true? The question is: who made the model?

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Walter Quattrociocchi @walter4c.bsky.social · 29/10/2025

Together, these papers suggest a transformation: → Knowledge is no longer verified, but simulated → Platforms no longer host views, they shape belief architectures → Truth is not disappearing. It’s being automated, fragmented, and rebranded

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Walter Quattrociocchi @walter4c.bsky.social · 29/10/2025

Paper 2 — Ideological Fragmentation of the Social Media Ecosystem We analyzed 117M posts from 9 platforms (Facebook, Reddit, Parler, Gab, etc). Some now function as ideological silos — not just echo chambers, but echo platforms. www.nature.com/articles/s41...

nature.com

Ideology and polarization set the agenda on social media - Scientific Reports

Scientific Reports - Ideology and polarization set the agenda on social media

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Walter Quattrociocchi @walter4c.bsky.social · 29/10/2025

Paper 1 — The Simulation of Judgment in LLMs We benchmarked 6 large language models against experts and humans. They often agree on outputs — but not on how they decide. Models rely on lexical shortcuts, not reasoning. We called this epistemia. www.pnas.org/doi/10.1073/...

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Walter Quattrociocchi @walter4c.bsky.social · 29/10/2025

We studied both, in two recent papers on @PNASNews and @PNASNexus : Epistemia — the illusion of knowledge when LLMs replace reasoning with surface plausibility Echo Platforms — when whole platforms, not just communities, become ideologically sealed

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Walter Quattrociocchi @walter4c.bsky.social · 29/10/2025

Two structural shifts are unfolding right now: Platforms are fragmenting into echo platforms — entire ecosystems aligned around ideology. LLMs are being used to simulate judgment — plausible, fluent, unverifiable.

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Walter Quattrociocchi @walter4c.bsky.social · 29/10/2025

#Grokipedia just launched. An AI-built encyclopedia, pitched as a “neutral” alternative to Wikipedia. But neutrality is not the point. What happens underneath is. 👇

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Walter Quattrociocchi @walter4c.bsky.social · 29/10/2025

timely, considering Grokpedia and all the related implications.

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Walter Quattrociocchi @walter4c.bsky.social · 21/10/2025

Don’t know your approach. Ours assumes that to understand the perturbation, you first need to operationalize the task and compare how humans and models diverge. That’s the empirical ground — not a belief about what LLMs “are.”

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Walter Quattrociocchi @walter4c.bsky.social · 20/10/2025

“LLMs don’t understand.” Of course. That was never the point. The point is: we’re already using them as if they do — to moderate, to classify, to prioritize, to decide. That’s not a model problem. It’s a systemic one. The shift from verification to plausibility is real. Welcome to Epistemia.

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Walter Quattrociocchi @walter4c.bsky.social · 19/10/2025

Coming from misinfo/polarization, we’re not asking what LLMs are. We’re asking: what happens when users start trusting them as if they were search engines? We compare LLMs and humans on how reliability and bias are judged. That’s where the illusion epistemia begins.

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Walter Quattrociocchi @walter4c.bsky.social · 19/10/2025

Yes, we include recent works on evaluation heuristics and bias in LLMs. Our focus is on how LLMs outputs simulate judgment. We compare LLMs and humans directly, under identical pipelines, on the same dataset. May rely is empirical caution. The illusion of reasoning is the point (not the premise).

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Walter Quattrociocchi @walter4c.bsky.social · 19/10/2025

Absolutely we build on that line. What we address is how these dynamics unfold now, at scale, where reliability is operationalized. The novelty isn’t saying “LLMs aren’t agents.” It’s showing how and when humans treat them as if they were. Plausibility replacing reliability. Epistemia.

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Walter Quattrociocchi @walter4c.bsky.social · 18/10/2025

Thank you for sharing. We explore the perturbation introduced when judgment is delegated to LLMs. We study how the concept of reliability is operationalized in (moderation, policy, ranking). Epistemia is a name for judgment without grounding. IMHO it is already here. (a new layer of the infodemic).

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Reposted by Walter Quattrociocchi

Proceedings of the National Academy of Sciences @pnas.org · 16/10/2025

LLMs can mirror expert judgment but often rely on word patterns rather than reasoning. A new study introduces epistemia, the illusion of knowledge that occurs when surface plausibility replaces verification. In PNAS: ow.ly/ry7S50Xcv9b

Prompt used for all LLMs when provided with the scraped HTML homepage.

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Reposted by Walter Quattrociocchi

CEU Department of Network & Data Science @ceu-dnds.bsky.social · 12/03/2025

📢Join us for a public lecture by @walter4c.bsky.social about the impacts of social media on society. ⛓️‍💥For online attendants, please register here: bit.ly/3FomgkF

Impact of Social Media on Society by Walter Quattrociocchi at the Department of Network and Data Science at the Central European University

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Walter Quattrociocchi @walter4c.bsky.social · 03/01/2025

5/ 💡 What does this mean? In the attention economy, chasing virality is risky. Instead, building consistent, sustained engagement is key to forming lasting connections with users.

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Walter Quattrociocchi @walter4c.bsky.social · 03/01/2025

4/ Rapid viral effects fade quickly, while slower, gradual processes last longer. This suggests that collective attention is elastic and influenced by pre-existing engagement trends. A "like" or viral post is often fleeting—it doesn’t guarantee long-term impact.

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Walter Quattrociocchi @walter4c.bsky.social · 03/01/2025

3/ Key findings: Viral events rarely lead to sustained growth in engagement. We identified two types of virality: 1️⃣ "Loaded" virality: The final burst after a growth phase, followed by a decline. 2️⃣ "Sudden" virality: Unexpected events that briefly reactivate user attention.

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Walter Quattrociocchi @walter4c.bsky.social · 03/01/2025

2/ 📊 We analyzed over 1000 European news outlets on Facebook & YouTube (2018-2023), using a Bayesian structural time series model. Our goal: Understand the impact of viral posts on user engagement, from short-term spikes to long-term trends.

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Walter Quattrociocchi @walter4c.bsky.social · 03/01/2025

1/ 🎉 First paper of 2025! In the quantitative study of the attention economy, we asked a key question: How much does a like—or a viral post—truly reverberate? Our new study, published in Scientific Reports, dives into this crucial topic. 🧵

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Walter Quattrociocchi @walter4c.bsky.social · 06/12/2024

5/ Implications: What does this mean for the future of language? Simplification can democratize communication but risks impoverishing public debate and cultural diversity. How can we balance accessibility with complexity?

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Walter Quattrociocchi @walter4c.bsky.social · 06/12/2024

4/ The role of platforms: Social media business models incentivize short, emotional, and easily shareable content. The result? Simpler but less rich language, shaped by the rules of engagement.

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Walter Quattrociocchi @walter4c.bsky.social · 06/12/2024

3/ Why it matters: Simplification of language may affect how we articulate and share ideas. Fewer words = fewer nuances? 👉 A risk for public debate, but also an adaptation to the digital age.

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Walter Quattrociocchi @walter4c.bsky.social · 06/12/2024

2/ Key findings: Language has simplified: shorter texts and less diverse vocabulary. Users continue to innovate, introducing new terms at a steady pace. These changes are platform-agnostic: a near-universal phenomenon.

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Walter Quattrociocchi @walter4c.bsky.social · 06/12/2024

1/ What we did: We collected 300 million English comments from platforms like Facebook, Twitter, Reddit, YouTube, and Telegram, covering data from 1990 to today. We measured: Lexical richness Text length Introduction of new words

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Walter Quattrociocchi @walter4c.bsky.social · 06/12/2024

Breaking News! Our latest paper has just been published in PNAS! 📄 We analyzed 34 years of data a cross 8 social media platforms to uncover how language has evolved in the digital age. 👉 Read the paper here www.pnas.org/doi/10.1073/...

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Walter Quattrociocchi @walter4c.bsky.social · 27/11/2024

5/ This segregation reshapes the digital public sphere, amplifies polarization, and limits dialogue across ideological divides. Our study provides a quantitative framework to understand these dynamics and inform policies to mitigate their societal impact.

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Walter Quattrociocchi @walter4c.bsky.social · 27/11/2024

4/ 📊 Our analysis on 126M URLs shared by 6M users,9 platforms, Facebook, Twitter, Reddit (mainstream) & Gab, Parler, BitChute (alt-tech). Alt-tech platforms are niches of ideological homogeneity & questionable content. Mainstream platforms are diverse but internally polarized.

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Walter Quattrociocchi @walter4c.bsky.social · 27/11/2024

3/ 🔬 We developed a framework to measure this fragmentation using three dimensions: 1️⃣ Centrality: Are platforms central or peripheral in the information ecosystem? 2️⃣ Content reliability: Reliable vs questionable news. 3️⃣ User base: Diverse vs homogeneous communities.

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Walter Quattrociocchi @walter4c.bsky.social · 27/11/2024

2/ Humans naturally group with like-minded peers. On social media, this tendency drives segregation, not just within communities but at the scale of entire platforms. We call this phenomenon Echo Platforms—platforms where ideological uniformity dominates.

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Walter Quattrociocchi @walter4c.bsky.social · 27/11/2024

1/ 🚨 New preprint on arXiv 🚨 "Characterizing the Fragmentation of the Social Media Ecosystem" arxiv.org/abs/2411.16826 @matteo_cinelli , @m_starnini edoardo di martino Alessandro Galeazzi #echoplatforms #fragmentation

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