William J. Brady
@williambrady.bsky.social
Assistant prof @ Kellogg School of Management, Northwestern University. Studying emotion, morality, social networks, psych of tech. #firstgen college graduate
Key result #3: Motive inferences were malleable: we developed an intervention that corrected peoples’ motive inferences - increasing people’s inference of behavioral motive to out-partisan caused them to be more willing to have a political conversation even in context of outrage
November 11, 2025 at 4:34 PM
Key result #3: Motive inferences were malleable: we developed an intervention that corrected peoples’ motive inferences - increasing people’s inference of behavioral motive to out-partisan caused them to be more willing to have a political conversation even in context of outrage
Key result #1: People largely reported their in-partisans’ (and their own) motives for outrage was to raise awareness or inspire action (behavioral motive), but thought political opponents motives were to shame or troll (contra-hedonic motive), which was a vast overestimation.
November 11, 2025 at 4:34 PM
Key result #1: People largely reported their in-partisans’ (and their own) motives for outrage was to raise awareness or inspire action (behavioral motive), but thought political opponents motives were to shame or troll (contra-hedonic motive), which was a vast overestimation.
In online experiments and a field study on Reddit, we asked users to report their motives for posting outrage and then had observers infer the motives.
November 11, 2025 at 4:34 PM
In online experiments and a field study on Reddit, we asked users to report their motives for posting outrage and then had observers infer the motives.
✨New preprint! Why do people express outrage online? In 4 studies we develop a taxonomy of online outrage motives, test what motives people report, what they infer for in- vs. out-partisans, and how motive inferences shape downstream intergroup consequences. Led by @felix-chenwei.bsky.social 🧵👇
November 11, 2025 at 4:34 PM
✨New preprint! Why do people express outrage online? In 4 studies we develop a taxonomy of online outrage motives, test what motives people report, what they infer for in- vs. out-partisans, and how motive inferences shape downstream intergroup consequences. Led by @felix-chenwei.bsky.social 🧵👇
The computational psych preconference is back @spspnews.bsky.social for a full day! This year's lineup:
👉theory-driven modeling: Hyowon Gweon
👉data-driven discovery: @clemensstachl.bsky.social
👉application: me
👉 panel: @steveread.bsky.social Sandra Matz, @markthornton.bsky.social Wil Cunningham
👉theory-driven modeling: Hyowon Gweon
👉data-driven discovery: @clemensstachl.bsky.social
👉application: me
👉 panel: @steveread.bsky.social Sandra Matz, @markthornton.bsky.social Wil Cunningham
September 29, 2025 at 4:57 PM
The computational psych preconference is back @spspnews.bsky.social for a full day! This year's lineup:
👉theory-driven modeling: Hyowon Gweon
👉data-driven discovery: @clemensstachl.bsky.social
👉application: me
👉 panel: @steveread.bsky.social Sandra Matz, @markthornton.bsky.social Wil Cunningham
👉theory-driven modeling: Hyowon Gweon
👉data-driven discovery: @clemensstachl.bsky.social
👉application: me
👉 panel: @steveread.bsky.social Sandra Matz, @markthornton.bsky.social Wil Cunningham
And here we are
September 28, 2025 at 5:06 PM
And here we are
@desmond-ong.bsky.social LLMs show context-insensitivity in empathetic responding which leads to comments rated as more inappropriate - can be harmful in therapeutic setting
May 7, 2025 at 6:08 PM
@desmond-ong.bsky.social LLMs show context-insensitivity in empathetic responding which leads to comments rated as more inappropriate - can be harmful in therapeutic setting
Jonas Dalege: minority groups can only influence if they have strong connections and the majority group doesn't have a strong belief network
#spsp2025 #comppsych
#spsp2025 #comppsych
February 20, 2025 at 6:02 PM
Jonas Dalege: minority groups can only influence if they have strong connections and the majority group doesn't have a strong belief network
#spsp2025 #comppsych
#spsp2025 #comppsych
@cinoolee.bsky.social: compiled 1000+ sm posts about racial discrimination and matched set on non-race topic...both AI and humans are sig more likely to flag posts about race for removal (36% more likely!) Triggered by identity threat + tone-policing
#spsp2025 #comppsych
#spsp2025 #comppsych
February 20, 2025 at 5:53 PM
@cinoolee.bsky.social: compiled 1000+ sm posts about racial discrimination and matched set on non-race topic...both AI and humans are sig more likely to flag posts about race for removal (36% more likely!) Triggered by identity threat + tone-policing
#spsp2025 #comppsych
#spsp2025 #comppsych
@gandalfnicolas.bsky.social: social groups are represented in LLMs in similar ways compared to human data, warmth and competence are key but only explain about 50% of variance (need more dimensions). #spsp2025 #comppsych
February 20, 2025 at 5:40 PM
@gandalfnicolas.bsky.social: social groups are represented in LLMs in similar ways compared to human data, warmth and competence are key but only explain about 50% of variance (need more dimensions). #spsp2025 #comppsych
Sanaz Talaifar: smart phone passive sensing study: Liberals have less fun than conservatives (they are on social media lot...). Also, people vastly overestimate daily routine differences among lib vs conservatives
#spsp2025 #comppsych
#spsp2025 #comppsych
February 20, 2025 at 5:03 PM
Sanaz Talaifar: smart phone passive sensing study: Liberals have less fun than conservatives (they are on social media lot...). Also, people vastly overestimate daily routine differences among lib vs conservatives
#spsp2025 #comppsych
#spsp2025 #comppsych
@curtispuryear.bsky.social a study of a decade of twitter posts shows and new measure of moralization shows that moralization has substantially increased over time (d = .45!). Driven by both self selection and within-user increase over time! #comppsych #spsp2025 (also stay tuned for this paper😎)
February 20, 2025 at 4:54 PM
@curtispuryear.bsky.social a study of a decade of twitter posts shows and new measure of moralization shows that moralization has substantially increased over time (d = .45!). Driven by both self selection and within-user increase over time! #comppsych #spsp2025 (also stay tuned for this paper😎)
Niyat Kachhiyapatel: LLM analysis of events in people's lives: people feel most uncertain during negative, emotional inducing events #comppsych #spsp2025
February 20, 2025 at 4:48 PM
Niyat Kachhiyapatel: LLM analysis of events in people's lives: people feel most uncertain during negative, emotional inducing events #comppsych #spsp2025
@madalina.bsky.social: sample of 63 countries test several interventions to increase climate policy support. Writing letter to future gen is best. Doom & gloom messaging great for increasing sharing but not for increasing support!
#spsp2025 #comppsych
#spsp2025 #comppsych
February 20, 2025 at 4:35 PM
@madalina.bsky.social: sample of 63 countries test several interventions to increase climate policy support. Writing letter to future gen is best. Doom & gloom messaging great for increasing sharing but not for increasing support!
#spsp2025 #comppsych
#spsp2025 #comppsych
Xavier Roberts-Gaal & @fierycushman.bsky.social: environmental variability predicts goal learning and stability predicts action learning in a really cool transmission experiment #spsp2025 #comppsych
February 20, 2025 at 4:21 PM
Xavier Roberts-Gaal & @fierycushman.bsky.social: environmental variability predicts goal learning and stability predicts action learning in a really cool transmission experiment #spsp2025 #comppsych
Gabriel Fajardo & @freemanjb.bsky.social have created a new connectionist model of trait formation (impression from faces). High dimension, dynamic models may buy us better model outcomes and situational variability #spsp2025 #comppsych
February 20, 2025 at 4:17 PM
Gabriel Fajardo & @freemanjb.bsky.social have created a new connectionist model of trait formation (impression from faces). High dimension, dynamic models may buy us better model outcomes and situational variability #spsp2025 #comppsych
Key result #3: A bridging algorithm that boosted bipartisan-liked content partially countered these misperceptions—yet it risked underrepresenting genuine disagreement. This reveals a complex tension between reducing polarization and maintaining accurate norm perception.
February 14, 2025 at 3:27 PM
Key result #3: A bridging algorithm that boosted bipartisan-liked content partially countered these misperceptions—yet it risked underrepresenting genuine disagreement. This reveals a complex tension between reducing polarization and maintaining accurate norm perception.
Key result #2: We also gauged participants perceptions of social norms after interacting with various feeds. Users in the engagement-based feds overestimated the descriptive and prescriptive norms for posting IME content ➡️ mediated greater posting intentions of blame content
February 14, 2025 at 3:27 PM
Key result #2: We also gauged participants perceptions of social norms after interacting with various feeds. Users in the engagement-based feds overestimated the descriptive and prescriptive norms for posting IME content ➡️ mediated greater posting intentions of blame content
Key result # 1: From natural user behavior as input, both passive and active engagement algorithms amplified IME posts disproportionately higher than their baserate in the network➡️ overrepresentation of IME content in feeds
February 14, 2025 at 3:27 PM
Key result # 1: From natural user behavior as input, both passive and active engagement algorithms amplified IME posts disproportionately higher than their baserate in the network➡️ overrepresentation of IME content in feeds
Method: Across 3 experiments (N = 6,107) users scrolled through content in mock social media environment. We measured passive (dwell time) and active (like/share) engagement to train algos, and manipulated content based on categories drawn from social learning theory
February 14, 2025 at 3:27 PM
Method: Across 3 experiments (N = 6,107) users scrolled through content in mock social media environment. We measured passive (dwell time) and active (like/share) engagement to train algos, and manipulated content based on categories drawn from social learning theory
👀New preprint! In 3 prereg experiments we study how engagement-based algorithms amplify ingroup, moral and emotional (IME) content in ways that disrupt social norm learning (and test one solution!) w/ @joshcjackson.bsky.social and my amazing lab managers
@merielcd.bsky.social
& Silvan Baier 🧵👇
@merielcd.bsky.social
& Silvan Baier 🧵👇
February 14, 2025 at 3:27 PM
👀New preprint! In 3 prereg experiments we study how engagement-based algorithms amplify ingroup, moral and emotional (IME) content in ways that disrupt social norm learning (and test one solution!) w/ @joshcjackson.bsky.social and my amazing lab managers
@merielcd.bsky.social
& Silvan Baier 🧵👇
@merielcd.bsky.social
& Silvan Baier 🧵👇
We think our model is an efficient way to explain public opinion in response to viral transgressions (see image below). Link to paper:
osf.io/preprints/os...
osf.io/preprints/os...
February 5, 2025 at 3:47 PM
We think our model is an efficient way to explain public opinion in response to viral transgressions (see image below). Link to paper:
osf.io/preprints/os...
osf.io/preprints/os...
✨New preprint✨How does repeated exposure to transgressions online shape moral judgment? Results show two competing processes:
💠We get desensitized = ⬇️ wrong
💠Transgression seems more infamous =⬆️wrong
Relative strength of each may predict outrage to viral transgressions w/ @danieleffron.bsky.social
💠We get desensitized = ⬇️ wrong
💠Transgression seems more infamous =⬆️wrong
Relative strength of each may predict outrage to viral transgressions w/ @danieleffron.bsky.social
February 5, 2025 at 3:47 PM
✨New preprint✨How does repeated exposure to transgressions online shape moral judgment? Results show two competing processes:
💠We get desensitized = ⬇️ wrong
💠Transgression seems more infamous =⬆️wrong
Relative strength of each may predict outrage to viral transgressions w/ @danieleffron.bsky.social
💠We get desensitized = ⬇️ wrong
💠Transgression seems more infamous =⬆️wrong
Relative strength of each may predict outrage to viral transgressions w/ @danieleffron.bsky.social
Findings, cont: outrage-evoking misinfo seems to be driven by non-epistemic motives. It is shared more without reading, and when news articles evoked outrage in our experiments it caused people to share more misinfo, even tho it did not impact ppl’s truth discernment!
November 28, 2024 at 7:07 PM
Findings, cont: outrage-evoking misinfo seems to be driven by non-epistemic motives. It is shared more without reading, and when news articles evoked outrage in our experiments it caused people to share more misinfo, even tho it did not impact ppl’s truth discernment!
Findings: misinfo consistently evokes more outrage than trustworthy news, and when it does it is shared more. This is specific to outrage - not just a general association with negative emotion in general
November 28, 2024 at 7:07 PM
Findings: misinfo consistently evokes more outrage than trustworthy news, and when it does it is shared more. This is specific to outrage - not just a general association with negative emotion in general