Preprint

Social Influence in the Academic Twitter Migration to Mastodon: A Computational Psychology Approach

This article is a preprint and has not been certified by peer review [What does this mean?].

Author(s) / Creator(s)

Bittermann, André
Lauer, Tim
Peters, Fritz

Abstract / Description

Social media is an essential tool for scholarly communication, yet dissatisfaction with platforms can drive researchers to migrate elsewhere, as seen in the shift from Twitter to Mastodon in late 2022, or more recently from X to Bluesky. Migrating researchers may exert influence on their colleagues to join them, but despite the growing importance of these migrations, the underlying social dynamics within academia remain poorly understood. Analyzing data from over 250,000 researchers, we used a machine learning model informed by social impact theory to identify key drivers of the 2022 academic Mastodon migration. Our findings reveal that the strongest predictor of platform migration was the number of followed peers discussing the move, rather than individual influential strength. Additionally, researchers endorsing open science principles were approximately eleven times more likely to migrate. These findings suggest that collective efforts, tailored to group characteristics, may foster behavior change interventions in science.

Keyword(s)

academic social networks researcher behavior group dynamics computational psychology of science metascience

Persistent Identifier

Date of first publication

2025-03-05

Publisher

PsychArchives

Citation

  • Author(s) / Creator(s)
    Bittermann, André
  • Author(s) / Creator(s)
    Lauer, Tim
  • Author(s) / Creator(s)
    Peters, Fritz
  • PsychArchives acquisition timestamp
    2025-03-05T07:25:03Z
  • Made available on
    2025-03-05T07:25:03Z
  • Date of first publication
    2025-03-05
  • Abstract / Description
    Social media is an essential tool for scholarly communication, yet dissatisfaction with platforms can drive researchers to migrate elsewhere, as seen in the shift from Twitter to Mastodon in late 2022, or more recently from X to Bluesky. Migrating researchers may exert influence on their colleagues to join them, but despite the growing importance of these migrations, the underlying social dynamics within academia remain poorly understood. Analyzing data from over 250,000 researchers, we used a machine learning model informed by social impact theory to identify key drivers of the 2022 academic Mastodon migration. Our findings reveal that the strongest predictor of platform migration was the number of followed peers discussing the move, rather than individual influential strength. Additionally, researchers endorsing open science principles were approximately eleven times more likely to migrate. These findings suggest that collective efforts, tailored to group characteristics, may foster behavior change interventions in science.
    en
  • Publication status
    other
  • Review status
    notReviewed
  • Persistent Identifier
    https://hdl.handle.net/20.500.12034/11569
  • Persistent Identifier
    https://doi.org/10.23668/psycharchives.16155
  • Language of content
    eng
  • Publisher
    PsychArchives
  • Is related to
    https://hdl.handle.net/20.500.12034/8557
  • Is related to
    https://hdl.handle.net/20.500.12034/9043
  • Keyword(s)
    academic social networks
  • Keyword(s)
    researcher behavior
  • Keyword(s)
    group dynamics
  • Keyword(s)
    computational psychology of science
  • Keyword(s)
    metascience
  • Dewey Decimal Classification number(s)
    150
  • Title
    Social Influence in the Academic Twitter Migration to Mastodon: A Computational Psychology Approach
    en
  • DRO type
    preprint
  • Leibniz institute name(s) / abbreviation(s)
    ZPID