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Alexandre Bovet

@abovet.bsky.social

Assistant Professor in Network Science at the University of Zurich - Networks, Computational Social Science, Complex Systems, Data Science He/Him

30 Posts367 Follower263 Folgt
Alexandre Bovet@abovet.bsky.social · 2mo ago

What's your favorite temporal network generation models? Yasaman Asgari and I are preparing a review and would like to be sure to cover the extensive literature on this topic. Let us know here: forms.gle/xrLBfAcWZVyR... or you can also just reply below.

Call for Articles: Temporal Network Generative Model Review

We (Yasaman Asgari & Alexandre Bovet) are preparing a review paper on temporal network generative models and would like to be sure to cover as most of the extensive literature. Please let us know of ...

forms.gle

Alexandre Bovet@abovet.bsky.social · 3mo ago

Interested in network science, evolutionary biology, and animal behavior? I am seeking a PhD student to join the Quantitative Network Science group at the Department of Mathematical Modeling and Machine Learning of the University of Zurich. Info and application here: jobs.uzh.ch/job-vacancie...

UZH: PhD in Network Science: Modeling of Animal Networks

We are seeking a highly motivated PhD student to join our Quantitative Network Science research group at the Department of Mathematical Modeling and Machine Learning at the University of Zurich. Wild ...

jobs.uzh.ch

GOTHAM lab@gotham-lab.bsky.social · 11mo ago

🎉 So excited to host the next CompleNet conference 🎉 Don’t miss it 👇 See you next May in Zaragoza!!!

𝙲𝚘𝚖𝚙𝚕𝚎𝙽𝚎𝚝 𝟸𝟶𝟸𝟽@complenet.bsky.social · 11mo ago

📢 Excited to announce CompleNet 2026! Join us to share your network science research in a highly interdisciplinary conference! 🗓️ 4–8 May 2026 | 📍 Zaragoza, Spain 🇪🇸 🚨 Call for contributions open – submit by Nov 15, 2025! 🌐 Info & registration: complenet.weeblysite.com

Yuan Zhang@yuan1227.bsky.social · 10mo ago

New publication with @abovet.bsky.social @esserfrank.bsky.social @laiacastro.bsky.social With today’s political environment becoming increasingly complex, how can political selective exposure be measured beyond the traditional ‘left vs. right’ lens? Read more: journals.plos.org/plosone/arti...

A multilevel network approach to revealing patterns of online political selective exposure

Selective exposure, individuals’ inclination to seek out information that supports their beliefs while avoiding information that contradicts them, plays an important role in the emergence of polarizat...

journals.plos.org

Elena Candellone@elenacandellone.bsky.social · 11mo ago

This paper is now published on Network Science! 🎊 Open-access published version: doi.org/10.1017/nws.... (and the dataset is freely available!) Menéame.net user interaction dataset: doi.org/10.5281/zeno... @javiergbe.bsky.social @abovet.bsky.social

Negative ties highlight hidden extremes in social media polarization | Network Science | Cambridge Core

Negative ties highlight hidden extremes in social media polarization - Volume 13

doi.org

Elena Candellone@elenacandellone.bsky.social · 2y ago

New preprint out! We analyze data from Meneame, a Spanish "Reddit-like" platform, assessing polarization with a dual method approach: SHEEP for signed networks and Correspondence Analysis for unsigned networks. doi.org/10.48550/arX...

Carl T. Bergstrom@carlbergstrom.com · last yr.

1. Kevin Gross and I just posted a new science-of-science preprint. This one explores the looming peer review crisis. As many of you know, it's becoming significantly more difficult for journal editors to find scholars willing to serve as peer reviewers for submitted manuscripts.

Will anyone review this paper? Screening, sorting, and the feedback cycles that imperil peer review

Scholarly publishing relies on peer review to identify the best science. Yet finding willing and qualified reviewers to evaluate manuscripts has become an increasingly challenging task, possibly even ...

arxiv.org

Vincent Traag@vtraag.bsky.social · last yr.

New preprint! 🚨 We study the interaction between misinformation and science on Twitter during COVID-19 based on ~407M tweets. Both science and misinformation featured prominently during the pandemic, but the interaction between the two has not been studied on this scale before. 🧵 (1/10)

Mapping the interaction between science and misinformation in COVID-19 tweets. Publication from @luzuzek.bsky.social, Juan Pablo Bascur, @annabertani.bsky.social, @ricgallotti.bsky.social. This project is supported by European Media and Information Fund. Abstract: During the COVID-19 pandemic, scientific understanding related to the topic evolved rapidly. Along with scientific information being discussed widely, a large circulation of false information, labelled an infodemic by the WHO, emerged. Here, we study the interaction between misinformation and science on Twitter (now X) during the COVID-19 pandemic. We built a comprehensive database of 407M COVID-19 related tweets and classified the reliability of URLs in the tweets based on Media Bias/Fact Check. In addition, we use Altmetric data to see whether a tweet refers to a scientific publication. We find that many users find that many users share both scientific and unreliable content; out of the 1.2M users who share science, also share unreliable content. Publications that are more frequently shared by users who also share unreliable content are more likely to be preprints, slightly more often retracted, have fewer citations, and are published in lower-impact journals on average. Our findings suggest that misinformation is not related to a ``deficit'' of science. In addition, our findings raise some critical questions about certain open science practices and their potential for misuse. Given the fundamental opposition between science and misinformation, our findings highlight the necessity for proactive scientific engagement on social media platforms to counter false narratives during global crises.