Onkar Sadekar

Dispersed female networks: female gorillas’ inter-group relationships influence dispersal decisions | Proceedings of the Royal Society B: Biological Sciences Dispersal is a fundamental aspect of many animal societies, impacting gene flow, knowledge transmission, culture and individual fitness. However, little is known about the information individuals use when dispersing. Mountain gorillas exhibit a flexible ...

So happy to see my first PhD paper out royalsocietypublishing.org/doi/10.1098/...

With my amazing supervisor @robinmorrison.bsky.social and the @savinggorillas.bsky.social, we examined female dispersal decisions in mountain gorillas.

Nominate a speaker for WiNS Seminar The Women in Network Science (WiNS) seminar is an interdisciplinary seminar with the aim to promote and showcase research by women and nonbinary researchers in network science. Attendance is open to e...

We are seeking speaker nominations for the Women in Network Science (WiNS) seminar series.

Let’s amplify diverse voices and break out of our usual bubbles.
Nominate someone inspiring today!

#WiNS #NetworkScience #WomenInScience

Applications are open for SFI's 2026 Complexity Postdoctoral Fellowships

If you’ve recently earned a Ph.D. in any scientific field and want to pursue independent, transdisciplinary research, consider applying.

Deadline: October 1, 2025
Apply here: santafe.edu/sfifellowship

Ethics in Complex Systems

Ethics in Complex Systems: A one-day workshop at the University of Zurich
ethics.dsi.uzh.ch/project/ethi...

🎥 All keynote talks from IC²S² ‘25 are now available on our YouTube channel!
#ic2s2 #css

IC2S2'25 Norrköping - YouTube This playlist contains all keynotes from IC2S2'25 in Norrköping, Sweden.

All the keynote recordings are available now, enjoy! www.youtube.com/playlist?lis...

DNDS at #IC2S2 2025 in Sweden

A strong presence at the top conference in computational social science!

10+ talks and posters by current & former members on networks, behavior, inequality and digital society.

#WeAreCEU #NetworkScience #SocialDataScience #SeeUatCEU

Prediction and explanation, together. Duncan Watts opened our final day with a keynote on “Integrating explanation and prediction in computational social science,” showing how pairing causal insight with predictive testing can push computational social science forward. #ic2s2

Seeing talk titles at #ic2s2 I can't be the only one, when reading LLM or AI, having to react with "oh, yet another one 🙄"? No disrespect to colleague's work, but the topic feels overhyped.. Not *everything* needs an LLM angle. #grinchmoment

Interested in the relationships between team dynamics, leadership dynamics, and success?

I’ll be presenting my poster today at #ic2s2 (poster #82).

Attending #ic2s2? My poster is up today!

👀 I’ll be presenting this work this week at @ic2s2.bsky.social (Thu, 11:00 AM · Social Media & Networks). If you’re there & interested, let’s connect! #IC2S2 N/N

🧵 New preprint!

Do online mental health communities form patterns of association that mirror diagnostic systems or challenge them?

“Network Analysis of Reddit Mental Health Communities: Mapping the Interconnectedness of Psychopathology”

👉 osf.io/7dfcw_v1

@ceu-dnds.bsky.social

Short thread: 1/N

🚨🚨 New preprint just dropped! In collaboration with @colltoaction.bsky.social, Cliff Joslyn, @fralotito.bsky.social, Audun Myers, Joshua Pickard, Brenda Praggastis, and Przemysław Szufel, we define a new data sharing standard for higher-order networks. arxiv.org/abs/2507.11520

Opinion dynamics: Statistical physics and beyond Opinion dynamics, the study of how individual beliefs and collective public opinion evolve, is a fertile domain for applying statistical physics to complex social phenomena. Like physical systems, soc...

Review "Opinion dynamics: Statistical physics and beyond"
arxiv.org/abs/2507.11521

Lab experiments, data, models, analytical/computational tools. 93 pages, >1k references.

With Fabian Baumann, David Garcia, Gerardo Iñiguez, Márton Karsai, Jan Lorenz, Katarzyna Sznajd-Weron. Led by Michele Starnini

How do social inequalities shape epidemic outcomes?

Our PhD alum Adriana Manna shares insights from her award-winning dissertation on contact patterns, vaccination gaps & a novel modeling framework.

📖 Interview: bit.ly/44uT6KF

#NetworkScience #EpidemicModeling

Our article “Evidence of equilibrium dynamics in human social networks evolving in time”, published in Communications Physics, is now featured on their homepage as part of their monthly selection of highlights! If you didn't read it yet, take a look!

www.nature.com/commsphys/

Diffusion of complex contagions is shaped by a trade-off between reach and reinforcement | PNAS How does social network structure amplify or stifle behavior diffusion? Existing theory suggests that when social reinforcement makes the adoption ...

Very pleased our paper looking at the diffusion of complex contagions is out in @pnas.org www.pnas.org/doi/10.1073/...

A meme of different kinds of generic network science papers

types of network science papers

PNAS special feature on Collective Artificial Intelligence and Evolutionary Dynamics

Contributions from scientists in machine learning, evolutionary game theory, and their growing intersection.

www.pnas.org/toc/pnas/122...

Drivers of cooperation in social dilemmas on higher‐order networks | Journal of The Royal Society Interface Understanding cooperation in social dilemmas requires models that capture the complexity of real-world interactions. While network frameworks have provided valuable insights to model the evolution of ...

Huge thanks to my brilliant collaborators, specially my supervisor
@fede7j.bsky.social
who has taught me so many things over the past few years!

Check out the open-access paper here:
🔗 royalsocietypublishing.org/doi/10.1098/...
@ceu-dnds.bsky.social

7/7

Our results suggest that social structure—especially higher-order and overlapping interactions—is central to sustaining cooperation.

This extends the evolutionary game theory toolkit for studying real group dynamics.

6/7

The outcome?

Higher cooperation levels across the board.

More structural overlap → more cooperation.

Coupled dynamics allow feedback across scales, enhancing coordination.

5/7

Our new model introduces:

✅ Group-size dependent strategies
✅ Tunable structural overlap between hyperedges
✅ Dynamical coupling between different interaction orders

It’s a more faithful representation of real collective dynamics.

4/7

But that model had key limitations:

🧠 Same strategy used across all group sizes
🔗 No structural overlap between different hyperedges

Both are unrealistic for many social and biological systems.

3/7

Group interactions—not just pairwise ones—shape how cooperation emerges in real-world social dilemmas.

In earlier work, we showed higher-order games on hypergraphs can boost cooperation under the right conditions.

📄 link.aps.org/doi/10.1103/...
2/7

Drivers of cooperation in social dilemmas on higher‐order networks | Journal of The Royal Society Interface Understanding cooperation in social dilemmas requires models that capture the complexity of real-world interactions. While network frameworks have provided valuable insights to model the evolution of ...

📢📢📢
Thrilled to share our new paper "Drivers of cooperation in social dilemmas on higher-order networks", out now in J. R. Soc. Interface! 🚀

With Andrea Civilini, Vito Latora & @fede7j.bsky.social

🔗 royalsocietypublishing.org/doi/10.1098/...
@dnds_ceu @ceu
1/7

People not only form social networks, they construct mental maps of them. People think about the ties between other people, including ties among individuals to whom they are not themselves directly connected. These “cognitive social networks” have rarely been studied. 1/

5-panel comic. (1) [teacher with long hair next to whiteboard] TEACHER: I’m supposed to give you the tools to do good science. (2) [teacher addressing students] But what *are* those tools? Methodology is hard and there are so many ways to get incorrect results. What is the magic ingredient that makes for good science? (3) TEACHER: To figure it out, I ran a regression with all the factors people say are important: [embedded list in sub-panel, cut off at end] Outcome variable: correct scientific results. Predictors: collaboration; skepticism of others’ claims; questioning your own beliefs; trying to falsify hypotheses; checking citations; statistical rigor; blinded analysis; financial disclosure; open data (4) TEACHER: The regression says two ingredients are the most crucial: 1) genuine curiosity about the answer to a question, and 2) ammonium hydroxide. (5) STUDENT: Wait, why did *ammonia* score so high? How did it even get on the list? LONG HAIR: ...And now you’re doing good science!

Good Science

xkcd.com/3101/

We are happy to announce the 3rd Workshop on Evolutionary Dynamics in social, cooperative and hybrid AI #EDAI2025 🤩
📍 Bologna, Italy at #ECAI2025
📆 October 25 or 26, 2025
🗞️ Submission deadline: 17 July 2025 23:59 CET
🔔 Workshop website: t.co/yiq4aWz75d