What predicts pro-MLM attitudes in a nationally representative US sample? TikTok use, not demographics, not politics.
Presenting "Platformed Persuasion" w/ Margaret Tait at #MPSA2026, Health Comms panel, Fri April 24 5:10 PM. Stop by if this sounds interesting to you - would love to connect!
PaCSS (Politics and Computational Social Science) is back! APSA preconference at BU joint with Political Communication, deadline for submission is May 8. Should be great!
cssi.umass.edu/pacss2026
Example of how Doc2Survey automatically converts a survey drafted in a Word/Google Doc to a fully programmed Qualtrics .qsf file.
Here's a simply example of how Doc2Survey automatically converts a survey drafted in Word/Google Doc into a fully programmed Qualtrics (.qsf) file, which is then ready to be launched. Available free to all researchers: www.verasight.io/doc2survey.
New in Nature Human Behaviour: How Deceptive Online Networks Reached Millions in the US 2020 Elections www.nature.com/articles/s41...
-Reached at least 37M Facebook and 3M Instagram users
-3 networks out of 49 responsible for >70% of users reached
-Exposed users older, more conservative
nice!
Screenshot of a paper titled “Contextualizing Misinformation: A User-Centric Approach to Linguistic and Topical Patterns in News Consumption,” authored by Ross Dahlke and colleagues. The abstract says the study uses web-browsing data from 1,240 U.S. adults during the 2020 election to compare misinformation and hard news. It finds that misinformation people consumed was generally easier to read, more negative in tone, and more morally framed, with substantial variation across topics and across groups such as older adults and Republicans.
Image description Two side-by-side horizontal bar charts compare topic distributions for hard news and misinformation. Hard news is led by general news at 35.9%, followed by U.S. electoral politics at 27.0%, social issues at 17.1%, COVID-19 at 14.2%, and health at 5.7%. Misinformation is much more concentrated in U.S. electoral politics at 53.0%, followed by social issues at 23.7%, COVID-19 at 11.6%, general news at 6.8%, and health at 4.9%.
Two stacked line charts show how topic shares changed over time from late August to early December 2020, with a vertical marker at Election Day 2020. In misinformation, U.S. electoral politics rises sharply in October and November and becomes the dominant topic around the election. In hard news, general news remains largest throughout, while U.S. electoral politics also spikes around Election Day before declining afterward.
Image description Two stacked line charts show how topic shares changed over time from late August to early December 2020, with a vertical marker at Election Day 2020. In misinformation, U.S. electoral politics rises sharply in October and November and becomes the dominant topic around the election. In hard news, general news remains largest throughout, while U.S. electoral politics also spikes around Election Day before declining afterward.
Most web browsing studies analyzing news and misinformation operate at the domain level. Work by me,
@fangjingtu.bsky.social et al., scrapes the content from web visits to go beyond the source to the content level, finding significant topical and linguistic variation doi.org/10.1145/3757571
Reciprocal political socialization within contemporary American families: Evidence from two randomized experiments April 23-26, 2026 | #MPSA2026 In Event: Speech and Political Expression Sun, April 26, 8 to 9:30 CDT Roberto F. Carlos et al University of Michigan Center for Political Studies
Children can influence their parents’ politics, especially on new issues. In diverse, tech-connected families, parents are receptive to political cues from their children, particularly on emerging topics like AI regulation. Don't miss @robertocarlos.bsky.social et al at #MPSA2026.
🚨New paper alert🚨 What happens when a polarized democracy bans a social media platform? New work with @cbarrie.bsky.social, Molly Roberts, Chris Schwarz, and @jatucker.bsky.social. We study Brazil's 2024 ban on X and find it created what we define as a "partisan sorting ratchet ." 1/
Pleased to see this one out in its JOP-formatted version @thejop.bsky.social www.journals.uchicago.edu/doi/10.1086/...
Can LLMs assist in the reliance on closed-ended questions in surveys?
In POQ, DiGiuseppe et al. find that LLMs have the potential to unlock the benefits of pairwise comparisons to scale open-ended responses.
Read now: doi.org/10.1093/poq/...
"While the median was low, we find substantial heterogeneity: individuals in the 90th percentile consume over 50 times the content of those in the 10th percentile."
papers.ssrn.com/sol3/papers....
New paper w/ @yamilrvelez.bsky.social! A lot of great research on political microtargeting discounts personalization: tailored ads (using AI or not) rarely beat a single-best message. We define two types of microtargeting, clarify when tailoring matters, & showcase a novel audio-based design.
New paper with Gabriela Czarnek, @dgrand.bsky.social and @adamberinsky.bsky.social out in Political Behavior! Link: link.springer.com/article/10.1...
Important new research shows the number of Americans who are neutral about democracy exceeds those who oppose it. These neutrals are NOT inattentive. They are: uninformed, cynical, ambivalent, conditional. @nathumbehav.nature.com
Democracy supporters speak out!
www.nature.com/articles/s41...
Looks like my book has a publication date - Misinformation and the Aging American coming from @academic.oup.com in October: global.oup.com/academic/pro...
A new study finds that anti-science influencers with real credentials are used to make misinformation look legitimate, organized groups of accounts boost their reach, and unreliable news outlets amplify the same bad information.
arxiv.org/pdf/2603.17249
Figure 1: Distribution of Brexit group affects among the Leavers and Remainers in each sample.
Figure 2: Overall Brexit in‐group bias.
Figure 3: Affective polarization and support for publication of Brexit in‐group and Brexit out‐group criticism. See Tables A2 and A22 in the Supplementary Material for full models.
The UK may have left the EU, but the two sides of the #Brexit debate are still PO'd. Phillips & Stoeckel explore the lingering animus Remainers & Leavers have toward each other & how those feelings manifest in political bias. Read their open-access article for their findings doi.org/10.1111/pops...
🧑💻 New paper at #chi2026 w @lorenzspreen.eurosky.social and @stefanherzog.bsky.social
Are you worried about how social media algorithms affect people’s beliefs? We are, so we tested engagement-based ranking algorithms against alternatives in a pre-reg’d collaborative filtering experiment... 🧵
1/ 🧵PROCESS Model 4 is the wrong tool to test mediation in an experiment. The c’ path turns prediction into description and prevents falsification. New preprint with @chriscarpenter.bsky.social and @beccafraz.bsky.social at osf.io/preprints/ps... explains why.
Interesting paper. When science is cheap, multiverse analysis becomes the key abstraction for authors & journals to strategize for.
These results suggest its the new unit of evidence authoring & review should accommodate.
Related to some of my comments here: substack.com/@jessicahull...
if focusing on tracked news use on platform, i think YouTube also skews older (e.g., sandragonzalezbailon.net/wp-content/u...) though seems less extreme than Facebook (e.g., journalqd.org/article/view...). but i wonder if self-reports might be capturing different news definitions across age groups
I am excited about this new paper, Negativity & Misinformation, just out with @cbwlezien.bsky.social in @polcommjournal.bsky.social: "durable biases in information processing, by media organizations and humans more generally, can produce misinformation and misperceptions..." doi.org/10.1080/1058...
no worries. I agree with that, btw, just curious about how the estimates would compare (a la the personality finding here www.pnas.org/doi/10.1073/...)
this looks interesting. was insincerity correlated with age in your sample? (eg www.pewresearch.org/short-reads/...) wondering if that could account for some portion of the pretty consistent age associations I've seen for violence
For those interested in measuring political violence, check out Lily and Nathan's new review paper below. See also my forthcoming paper at POQ (w/ @llopez.bsky.social and Lucas Lothamer) introducing our own measure scottaclifford.com/wp-content/u...
P.S. Pre-post differences are *not* valid treatment effect estimates. Why? Here's a post by @statsepi.bsky.social: statsepi.substack.com/p/one-simple..., here's a post by me: www.the100.ci/2025/01/22/r... >
Stack of four copies of the book "Teaching Political Communication"
'Teaching Political Communication' is now available! More than 40 contributors offer crucial pedagogical reflections, practical insights, and a host of creative activities and approaches to try out. Details here: www.e-elgar.com/shop/usd/tea...
Acquiescence Bias and Criterion Validity: Problems and
Potential Solutions for Agree-Disagree Scales link.springer.com/article/10.1...
@scottclifford.bsky.social & @amengel.bsky.social
seems important
Interesting diary study in Australia:
"Everyday encounters with misinformation online"
www.tandfonline.com/doi/pdf/10.1...
Causal mediation designs are beginning to trickle into comm journals. Encouraging to see!
Beliefs as causal mediators in the design of communication interventions academic.oup.com/hcr/article-...
But Is That Mediator Really the Cause? journals.sagepub.com/doi/10.1177/...