| ActivityPub | @[email protected] |
| Threads | @3udaemon/@threads.net |
| Bluesky | https://johnlam.BSKY.social |
| @[email protected] |
The Xitter Xodus, Mastodon instances, Bluesky nova, and Brid.gy gateways got your feeds all jumbled? Try https://surf.social from Flipboard, one of the first feed aggregators on social, and reunite the fractured dialogue.
When will we recognize the emergency ever so unnoticeably boiling our seas and wringing our skies?
When will we stop criticizing cyclists who fear the crush of cars and bang on the halls of city council for want of safe infrastructure?
When will we bash and smash supersized supertrucks like United Auto Workers bashed Hondas and Toyotas in the previous never-so-dire gas emergency?
Lest we not think it’s an emergency… @berkeleylab
https://x.com/berkeleylab/status/1840892738281107813
https://t.co/iT8SDUG9PO
In their @uwcip rapid research report, Caulfield and Starbird also examined Twitter/X discourse around the Lahaina fires on Maui. They write: "Both during the fires themselves and in the aftermath, X discourse has leaned into conspiracism, with much of the discourse centering around theories the fires may have been deliberate." [3/3]
Read their report: https://www.cip.uw.edu/2023/08/31/youtube-lahaina-wildfires-causes/
#UWCIP #Wildifires #Misinformation #MisinformationResearch #SocialMedia #Maui #Lahaina
The Lahaina wildfires were still raging as the first questions about whether they might have been “deliberately set” emerged online. Though all current evidence points to an accidental start, poten…
🚨 📢 Ever wondered what drives mass migration on social media platforms? 🤔 We just posted a preprint (w/ @lajello and @andreatagarelli analyzing the #TwitterMigration 🐦 to #Mastodon 🐘 after Elon Musk's acquisition! 🚀
Our analysis of the social network and public conversations of 75K migrated users reveals social influence dynamics akin to a compartmental epidemic model of information diffusion. 📈🔬
📚 https://arxiv.org/abs/2305.19056
@networkscience @computationalsocialscience @complexsystems
The migration of Twitter users to Mastodon following Elon Musk's acquisition presents a unique opportunity to study collective behavior and gain insights into the drivers of coordinated behavior in online media. We analyzed the social network and the public conversations of about 75,000 migrated users and observed that the temporal trace of their migrations is compatible with a phenomenon of social influence, as described by a compartmental epidemic model of information diffusion. Drawing from prior research on behavioral change, we delved into the factors that account for variations across different Twitter communities in the effectiveness of the spreading of the influence to migrate. Communities in which the influence process unfolded more rapidly exhibit lower density of social connections, higher levels of signaled commitment to migrating, and more emphasis on shared identity and exchange of factual knowledge in the community discussion. These factors account collectively for 57% of the variance in the observed data. Our results highlight the joint importance of network structure, commitment, and psycho-linguistic aspects of social interactions in describing grassroots collective action, and contribute to deepen our understanding of the mechanisms driving processes of behavior change of online groups.
David King
Brent Toderian
John Lam
Center for an Informed Public
Lucio La Cava