Manuel Tonneau

PhD candidate in Social Data Science @OIIOxford. NLP, Computational Social Science @WorldBank, 🐘 @[email protected]. 🇫🇷 🇪🇺

[Manuel Tonneau @ManuelTonneau]

Can we detect #hatespeech at scale on social media?

To answer this, we introduce 🤬HateDay🗓️, a global hate speech dataset representative of a day on Twitter.

The answer: not really! Detection perf is low and overestimated by traditional eval methods

https://t.co/OznvktglzK
🧵

[Paul Röttger @paul_rottger]

New paper w/ @AISecurityInst: AI writing assistance distorts how others perceive AI users and their opinions.

Millions of people now use AI to help them write and communicate. In three large experiments (14k participants, 3m+ human ratings) we show that AI writing assistance systematically distorts writer personas – their perceived beliefs, personality, and identity. These distortions are consistent across AI models and persist even under realistic conditions of human oversight.

🧵

[Manuel Tonneau @ManuelTonneau]

Thanks also to @JohnHolbein1 whose numerous posts on demographic probing in the social sciences inspired this work and to Matthew Kearney for the useful benchmark dataset.

[Manuel Tonneau @ManuelTonneau]

Demographic cues (eg names, dialect) are widely used to study how LLM behavior may depend on user demographics. They are often assumed interchangeable

🚨We show they are not: different cues yield different model behavior for the same group and different conclusions on LLM bias🧵

[Manuel Tonneau @ManuelTonneau]

Lots more info in the paper: https://t.co/XnzFwn8eLj

I had a blast working on this with my wonderful coauthors @sehgal_neil @niyati_malhotra @vicorozc Ana Maria, Lakshmi @sharathguntuku @vjhofmann.

Feedback welcome!

[Sam Fraiberger 🔎🌍 @spfraib]

New paper out in @PNASNexus

We show how skewed social media data can still be used to reliably estimate unemployment, not just nationally but down to the city level. 📈

https://t.co/KK18GlY1Sb

1/N

[Oxford Internet Institute @oiioxford]

ICYMI: Listen to @ManuelTonneau @oiioxford’s interview with the @SOEPTech podcast talking about his new research into hate speech, online platforms and disparities in content moderation across different European countries. More here: https://t.co/QhcKr1P0tP

[Hannah Rose Kirk @hannahrosekirk]

Conversational AI is fast becoming a key information source for humans worldwide, including during election cycles.

But what are the effects on users' epistemic health? 🧠

🚨Today we released new @AISecurityInst evidence that brings cautious optimism for LLMs vs internet search

[Oxford Internet Institute @oiioxford]

@TheMediaLeader highlights new insights from @ManuelTonneau, @deeliu97, Prof. @ralphschroeder and Prof. @computermacgyve, whose research found that 16mn EU-based users of X “do not have moderators for their national language” — equivalent to 14% of the platform’s EU user base.

[Rasmus Kleis Nielsen @rasmus_kleis]

Millions of users are posting to social media and other platforms in languages with zero moderators, even within the EU.

That's the topline finding from a working paper leveraging newly mandated transparency data under the DSA led by @ManuelTonneau https://t.co/DLuMQrUcMB

[Manuel Tonneau @ManuelTonneau]

@oiioxford @JWI_Berlin @UCPH_Research @UMassAmherst @umsi @meedan

[Manuel Tonneau @ManuelTonneau]

Social media platforms operate globally, but do they allocate human moderation equitably across languages?

Answer: no!
-Millions of users post in languages with 0 mods
-Where mods exist, mod count relative to content volume varies widely across langs

https://t.co/VPfgRnKraM

[Manuel Tonneau @ManuelTonneau]

Finally tagging scholars whose work inspired this piece: @monaelswah @FarhanaShahid_ @NicProllochs @CatalinaGoanta @s_cresci Your feedback is most welcome!