Morgan Wack

PostDoc @uzh_ikmz. Formerly @ClemsonHub & @UW. Technology & democracy, political misinformation, African politics, and LFC.

[Verasight @verasight_data]

"We see only about an 8% rate of... true fact-checks in the data that we look at."

@MorganWack, a postdoctoral scholar at the University of Zurich (@uzh_ikmz), on a new working paper with Patrick Warren, "Fact-check? True!: Tracking Verification Requests and the Absence of Truth Verdicts across Correction Systems."

Wack and Warren's paper uses Verasight data. Read the full paper here: https://t.co/YcFWUjPnLV

Watch the full interview on YouTube: https://t.co/BxpSGlD13E

[Lucas Paulo da Silva @Lucas_P_daSilva]

Today is the opening day of the #World #Cup.⚽️We're excited to announce our paper "Football Empires: Simulating the Effects of Colonialism on the 2026 World Cup" (with Thomas Schincariol and
@MorganWack)!

Check it out here: https://t.co/BIOSSQBJ2L

(see more info👇)

[Kiran Garimella @gvrkiran]

As one would expect, a weak point in Community Notes is that the crowd is more likely to flag claims that are easy to debunk, and less likely to act on plausible misinformation that takes real work to check.

This systematically biases what is corrected.

https://t.co/JmMYjmiYjY

[Morgan Wack @MorganWack]

Preprint available now 👉
https://t.co/IQ6SeMpJwk

Feedback welcome!

[Morgan Wack @MorganWack]

🧵Excited to share a new preprint (summary below)

"Fact-Checks Can Help Inoculate LLMs Against Disinformation"

w/Eva-Maria Vogel, @christianpipal, & @plwarre

https://t.co/IQ6SeMpJwk 👇

[Morgan Wack @MorganWack]

🧩 Fact-checkers have long struggled with reach. Our findings suggest they have an unrecognized second audience. A correction that enters a model's training data shapes the response delivered to every user who queries that topic.

[Darren Linvill @DarrenLinvill]

Check out Spot the Troll 2.0, out today from our team at @ClemsonHub.

Our updated quiz tests if you can spot fake social media accounts . . . of if you get trolled.

Many thanks for their work on this, but especially @interactiveknow and @knightfdn

https://t.co/s8ciV7iOse

[Morgan Wack @MorganWack]

🔎 Want to know more about how policies can influence the spread of election narratives?

My new article interrogating this topic, written alongside an talented team from the CIP, is out now at @PSJ_Editor! Access via the link ⬇️

[PSJ (@psjeditor.bsky.social) @PSJ_Editor]

EARLY VIEW ALERT

Ballot processing delays = more misinformation? Dive into this PSJ Early View article showing how restrictions on ballot processing fueled false narratives on X/Twitter after the 2020 U.S. election.

Read here: https://t.co/a0oYF0eyqQ

#PSJ #PolicyStudiesJournal

[Darren Linvill @DarrenLinvill]

The Russian propaganda account @its_The_Dr recently posted a fascinating story about "the pedophile church of Ukraine," citing a website called the New Zealand Times.

You won't be surprised to hear the website is a fake. It doesn't even have any news from New Zealand!
1/3

[PsyPost.org @PsyPost]

A pro-Kremlin influence campaign used AI to boost disinformation output without undermining credibility, according to new research. https://t.co/4cbIfLXoOv

[PNAS Nexus @PNASNexus]

A study of a Russian-backed propaganda outlet finds that AI is already being used to enhance messaging and expand disinformation campaigns, raising concerns about its growing impact on global influence operations.

In @Physorg_com: https://t.co/HF0YF3P4cP

[PNAS Nexus @PNASNexus]

A study of a propaganda site with ties to Russia shows that using AI allows propagandists to dial up the volume of their content without sacrificing persuasiveness. The authors call for action to combat the threat. In PNAS Nexus: https://t.co/dXmPChRzlp

[Morgan Wack @MorganWack]

Here is the link to the full (open source) paper! 🔗

https://t.co/noZ2jOa1HR

We welcome feedback & potential collaboration focused on how to counter emerging AI-driven disinformation campaigns!

[Morgan Wack @MorganWack]

Finding One 📝: AI use significantly increased the quantity of disinformation. This aligns with the idea that generative models reduce the cost/time of writing, editing, and curating. Once the site adopted LLM tools, weekly post counts soared. 4/

[Morgan Wack @MorganWack]

Finding Three 📝: Even with the shift to AI, the persuasive potential and credibility of the articles persisted. This finding suggests that even in rapid scaling article production the website did not need to sacrifice its perceived authenticity or potential impact. 6/

[Morgan Wack @MorganWack]

We focus on a site identified by @ClemsonHub that presented itself as a genuine U.S. news outlet but which was actually part of a Russian-affiliated influence operation. By pinpointing a transition away from human-editing to LLM-edited content, we show: 3/

[Morgan Wack @MorganWack]

📢 Excited to see our new paper out at @PNASNexus w/@plwarre, @DarrenLinvill, & Carl Ehrett!

Using data from a Russia-backed influence operation running puppet website DCWeekly, we show how LLMs are being used to scale global disinfo campaigns: 1/ 🧵
https://t.co/GneQgYswXT