Martin Saveski
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msaveski.bsky.social
Martin Saveski
@msaveski.bsky.social
1.2K followers 680 following 40 posts
Assistant Professor @ UW iSchool. Interested in computational social science, social networks & causal inference.
http://martinsaveski.com
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msaveski.bsky.social
Decreasing exposure to AAPA made participants less angry and sad in the moment while increasing exposure had the opposite effect. The reranking didn’t have any effect on calm and excitement.

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Effects of reducing and increasing exposure to AAPA content in participants’ feeds on their experiences of emotion compared with that of the corresponding control group. (Left) Participants were surveyed within the feed during the intervention [scale ranged from 0 (“none at all”) to 100 (“extremely”)] and (right) off-platform after the experiment [scale ranged from 1 (“never”) to 5 (“all the time”)]. The filled circles represent statistical significance (Padj < 0.05, adjusted for multiple hypothesis testing), and the error bars represent 95% CIs.
December 1, 2025 at 7:59 AM
msaveski.bsky.social
While the effects are symmetric, it’s worth noting that we upranked a few APAA posts and downranked all AAPA posts in the corresponding conditions.

/8
Average fraction of AAPA posts seen by participants for each day of the experiment.
December 1, 2025 at 7:59 AM
msaveski.bsky.social
In a field experiment with 1,256 consenting participants, we found that downranking AAPA posts leads to a decrease and upranking to an increase in affective polarization of 2 degrees on the 0-100 out-party feeling thermometer.

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Effects of reducing and increasing exposure to AAPA content in participants’ feeds on their feeling toward the out-party relative to the corresponding control group. (Left) Participants were surveyed within the feed during the intervention and (right) off-platform after the experiment. The feeling thermometer scale was between 0 (cold) and 100 (warm). The error bars represent 95% CIs.
December 1, 2025 at 7:59 AM
msaveski.bsky.social
New paper in Science:

In a platform-independent field experiment, we show that reranking content expressing antidemocratic attitudes and partisan animosity in social media feeds alters affective polarization.

🧵
Today, social media platforms hold the sole power to study the effects of feed-ranking algorithms. We developed a platform-independent method that reranks participants’ feeds in real time and used this method to conduct a preregistered 10-day field experiment with 1256 participants on X during the 2024 US presidential campaign. Our experiment used a large language model to rerank posts that expressed antidemocratic attitudes and partisan animosity (AAPA). Decreasing or increasing AAPA exposure shifted out-party partisan animosity by more than 2 points on a 100-point feeling thermometer, with no detectable differences across party lines, providing causal evidence that exposure to AAPA content alters affective polarization. This work establishes a method to study feed algorithms without requiring platform cooperation, enabling independent evaluation of ranking interventions in naturalistic settings.
December 1, 2025 at 7:59 AM
msaveski.bsky.social
Looking forward to giving a tutorial on Social Media Feed Ranking Algorithms with @tiziano.bsky.social at @icwsm.bsky.social today! Come join us at AAU, Room 2.1.083.
Title slide for an ICWSM tutorial titled "Social Media Feed Ranking Algorithms: Guide to Field Experiments" by Tiziano Piccardi and Martin Saveski, featuring stylized social media posts and an alert icon highlighting emotionally engaging content.
June 23, 2025 at 7:58 AM
msaveski.bsky.social
[Please reshare]
I’m recruiting PhD students to work with me at UW!

I’m looking for students passionate about developing new *social media algorithms*, both broadly and within the scope of this NSF grant: tinyurl.com/395yfphd

More info: faculty.washington.edu/msaveski/

cc @uwischool.bsky.social
UW campus, Drumheller Fountain and Rainier Vista.
November 13, 2024 at 9:10 AM