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Latest Publications


June 2026
BioRxiv
Sinha M, Yu B, Mendes da Silva R, Roelleke U, Luley P, Tiburcy M, Zimmermann WH, Burghammer M, Koester S
May 2026
The New England Journal of Medicine
Zimmermann WH, Ensminger S, Kutschka I, Paitazoglou C, Seidler T, Brandenburg S, Anker SD, Bader N, Bergau L, Bremmer F, Diogo PG, Eitel I, Fujita B, Gerecke B, Hasenfuß G, Hellenkamp K, Hermann-Lingen C, Jebran AF, Jurczyk D, Knaus R, Legler T, Lotz J, Placzek M, Pühler T, Riggert J, Sadlonova M, Saraei R, Ströbel P, Tiburcy M, Ullrich C, Voigt JU, Walker F, Wollnik B, Yigit G, Friede T; BioVAT-HF Investigators
May 2026
Glia
Moore S, Subramanian S, Meschkat M, Hemesath JW, Ruhwedel T, Möbius W, Nave KA, de Hoz L
May 2026
Science Translational Medicine
Saw RS, Haas S, Schmidt F, Ryazanov S, Leonov A, Bleher D, Grotegerd AK, Kuebler L, Roeben B, Schmidt F, Reimold M, Bonanno F, Ruf VC, Dahl B, Sandiego CM, Henry KE, Papadopoulos I, Schaller M, Kahle PJ, Levin J, Gasser T, Brockmann K, Reischl G, la Fougère C, Pichler BJ, Maurer A, Griesinger C, Giese A, Herfert K
May 2026
Arxiv
Brockers VC, Ventzke RD, Neuhaus V, Hidalgo-Ogalde B, Priesemann V
May 2026
Nature Communications
Szöllősi D, Pratihar S, Mukhopadhyay D, Rout AK, Han M, Reddy GJ, Ebersberger N, Becker S, Nagy G, Rauscher S, Lee D, Klement R, Griesinger C, Grubmüller H
May 2026
BioRxiv
Koert E, Götz J, Albrecht N, Vavakou A, Wolf BJ, Moser T
May 2026
BioRxiv
Albrecht N, Koert E, Vavakou A, Roos L, Jablonski L, Marcoleta JP, Cardona Audi J, Alfken J, Aakhte M, Klein E, Salditt T, Huisken J, Ruther P, Mager T, Kusch K, Moser T
May 2026
Nature Communications
Yoshida M, Gersteuer F, Berendes O, Fujiwara K, Safdari HA, Paternoga H, Takada H, Obana N, Grubmüller H, Bock LV, Wilson DN, Chiba S
May 2026
Arxiv
Golovin A, Mohr SB, Gottwald AI, Hvid U, Trivedi S, Neto JP, Schneider AC, Priesemann V

Authors

Golovin A, Mohr SB, Gottwald AI, Hvid U, Trivedi S, Neto JP, Schneider AC, Priesemann V

Journal

Arxiv

Citation

arXiv:2605.15956

Abstract

Here we present a massive longitudinal dataset of public Telegram content, comprising over 5.9 billion messages dating from 2015 to 2025, collected from 712 thousand channels and groups, enriched with metadata on forwards, reactions, and polls. The dataset spans multiple languages including Russian and Farsi, representing countries where Telegram shows mainstream adoption, as well as Western languages where Telegram is used in specific sub-communities. The dataset has several advantages. First, when restricted by language, it provides a versatile example of an algorithm-free platform, contrary to many other social media platforms that are strongly influenced by opaque content-curation algorithms. Second, it enables comparative studies across different languages, communities, and user bases under identical platform affordances. The dataset thus offers a foundation for studying engagement patterns, network evolution, and community formation in the absence of algorithmic curation.

DOI

10.48550/arXiv.2605.15956

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