Uncovering simultaneous breakthroughs with a robust measure of disruptiveness An embedding-based disruption measure not only robustly captures disruptive works but also reveals simultaneous discoveries.

The Higgs mechanism was proposed in 1964 by three independent teams.

But here is the puzzle🤔: the "disruption index" says Higgs's paper is among the least disruptive ever.

So what is going on?

In our new paper, just out in #ScienceAdvances, we take up this puzzle: doi.org/10.1126/scia... 👇

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Strongly clustered random graphs via triadic closure: Degree correlations and clustering spectrum Real-world networks often exhibit strong transitivity with nontrivial local clustering spectra and degree correlations. Such features are not easily modelled in tractable network models, creating an o...

Strongly clustered random graphs via triadic closure: Degree correlations and clustering spectrum arxiv.org/abs/2603.04669

Deep Generative Model for Human Mobility Behavior Understanding and modeling human mobility is central to challenges in transport planning, sustainable urban design, and public health. Despite decades of effort, simulating individual mobility remains...

Deep Generative Model for Human Mobility Behavior arxiv.org/abs/2510.06473

Excited for the Networks of Science of Science satellite at NetSCI 2026 this year in Boston!

netscisci.github.io

Be sure to submit by March 4th!

[New paper!] Mobility data are incredibly powerful, but also come with a long list of well-known biases (sampling, coverage, demographics, behavioral, etc.). In the paper, we survey them all and then zoom in on one that has been surprisingly underexplored: temporal bias.

arxiv.org/abs/2601.22330

Finally, our paper is published in Physical Review E! Surprisingly, the anomalous network-dependent properties observed in ordinary percolation are washed out by the shortest-path-percolation process!

An updated arXiv preprint will be available soon as well.

🔗: journals.aps.org/pre/abstract...

✨ Excited to announce 𝗬𝗼𝗻𝗴-𝗬𝗲𝗼𝗹 (𝗬𝗬) 𝗔𝗵𝗻 as a NetSci 2026 Plenary Speaker! A leading network and data scientist, YY explores how complex systems shape behavior, cognition, and discovery. Stay tuned for more speaker updates as we build toward an inspiring NetSci 2026! ✨
www.netsci2026.com/speakers

The Effects of Remote Working on Scientific Collaboration and Impact The COVID-19 pandemic shifted academic collaboration from in-person to remote interactions. This study explores, for the first time, the effects on scientific collaborations and impact of such a shift...

The Covid pandemic accelerated an ongoing shift towards remote working. Plus: scientists frequently collaborate with people from other institutions. Minus: paper impact decreased (are online interactions less creative?). @satyakisikdar.bsky.social @ftudisco.bsky.social arxiv.org/abs/2511.18481

Signed Networks: theory, methods, and applications Signed networks provide a principled framework for representing systems in which interactions are not merely present or absent but qualitatively distinct: friendly or antagonistic, supportive or confl...

Our team just released a comprehensive and accessible review of Signed Networks — two years in the making! Theory, methods, applications, all in one place. Feedback welcome.
arxiv.org/abs/2511.17247

📢How should authors go about putting the point-by-point response to reviewers' document together, in order to make the process smoother and more efficient for authors, editors, and reviewers? Check out our latest Editorial! www.nature.com/articles/s43... #SciencePublishing #ResearchPublishing

Two variants of the friendship paradox: The condition for inequality between them The friendship paradox -- the observation that, on average, one's friends have more friends than oneself -- admits two common formulations depending on whether averaging is performed over edges or ove...

Two variants of the friendship paradox: The condition for inequality between them arxiv.org/abs/2511.06176 a small experimental scientific communication project, encouraged by @socph.bsky.social

I'm looking for a PhD student to join my lab at UAlbany for Fall 2026!

We are data scientists studying the creation, flow, and impact of information. How do scientists collaborate? How does AI shape information access? What drives local innovation?

Want to answer these questions? details below!

Report: Mapping LLM Tools for Public Discourse, Pluralism & Social Cohesion Announcing a map produced by participants in the LLMs for Public Discourse convening

Interested in how LLM tools are being creatively used for good?

Check out this map of LLM Tools for Public Discourse, Pluralism & Social Cohesion.

Bonus: link to a public dataset of 70+ tools is included in the first page of the report.

Scale invariance and statistical significance in complex weighted networks Most networks encountered in nature, society, and technology have weighted edges, representing the strength of the interaction/association between their vertices. Randomizing the structure of a networ...

When you randomize a weighted network, be careful! Results may depend on the unit used for the weights, particularly when you want to know if they are statistically significant. Check our paper, just out on the arXiv. @skojaku.bsky.social @filipisilva.bsky.social
arxiv.org/abs/2510.23964

The Physics of News, Rumors, and Opinions The boundaries between physical and social networks have narrowed with the advent of the Internet and its pervasive platforms. This has given rise to a complex adaptive information ecosystem where ind...

The Physics of News, Rumors, and Opinions arxiv.org/abs/2510.15053

Dynamical Phase Transitions in Nonequilibrium Networks link.aps.org/doi/10.1103/...

This month, no colloquium but a special session about careers in network science! Join us and an all-star panel on October 29. Register here for a Zoom link: iu.zoom.us/webinar/regi...

New preprint! 🚀 We ask: What happens when you bring human team science into the design of multi-agent LLM systems? In particular, how do team structure, diversity, and interaction dynamics influence how AI agents collaborate?
📄Full Paper: arxiv.org/pdf/2510.07488
👩‍💻Code: github.com/Rasikamurali...

Modeling the spatial growth of cities The growth of cities has traditionally been studied from a population perspective, while urban sprawl - its spatial growth - has often been approached qualitatively. However, characterizing and modeli...

Modeling the spatial growth of cities arxiv.org/abs/2510.03045

GitHub - skojaku/tobibtex Contribute to skojaku/tobibtex development by creating an account on GitHub.

One of the time-consuming tasks in paper writing is to curate bibtex for references. So I automated bibtex curation with an Alfred app that fetches entries from dx.doi.org using DOI or title. It saves time, reduces errors, and maintains consistent LaTeX keys. github.com/skojaku/tobi...

Network connectivity analysis via shortest paths
https://arxiv.org/abs/2509.03230

Shortest-path percolation on scale-free networks The shortest-path percolation (SPP) model aims at describing the consumption, and eventual exhaustion, of a network's resources. Starting from a graph containing a macroscopic connected component, ran...

Strikingly, the shortest-path percolation homogenizes scale-free networks before the phase transition, resulting in the same universality class as the Erdős–Rényi Networks!

Check out our new preprint on arXiv: arxiv.org/abs/2509.09142

Unfortunately, Bloomington is missing 🌽😅

Modeling resource consumption in the US air transportation system via minimum-cost percolation - Nature Communications Percolation frameworks have been used to characterize the robustness of infrastructural networks. Here, authors introduce a percolation-based framework to study resource consumption and network effect...

Q: How are resources consumed in transportation networks, and how does this shape the overall functioning of the system?

We introduce the minimum-cost percolation framework and apply it to the U.S. air transportation system using publicly available data.

🔗 www.nature.com/articles/s41...

Hierarchical organization of bursty trains in event sequences Temporal sequences of discrete events that describe natural and social processes are often driven by non-Poisson dynamics. In addition to a heavy-tailed interevent time distribution, which primarily c...

Happy to share this long-overdue project! We found that many real-world event sequences follow a surprisingly similar hierarchically structured pattern, and that multi-timescale memory mechanisms can explain this pattern. Feedback welcome!
arxiv.org/abs/2508.18281

Anatomy of a Swedish population-scale network - Scientific Reports Scientific Reports - Anatomy of a Swedish population-scale network

🧮 ~8M nodes, 330M relationships across family, household, school & work.

🇸🇪 We constructed a multilayer population-scale network for Sweden, capturing distinct features of the country.

📝 doi.org/10.1038/s415...

cc: @ingakwoh.bsky.social @matmagnani.bsky.social ++

The psychophysics of style - Nature Human Behaviour Drawing on methods from psychophysics across ten experiments, Boger and Firestone examine the cognitive and computational foundations of style perception. Their findings suggest that this capacity is ...

The psychophysics of style www.nature.com/articles/s41...

The Trade-Off between Directness and Coverage in Transport Network Growth Designing spatial networks, such as transport networks, commonly deals with the problem of how to best connect a set of locations through a set of links. In practice, it can be crucial to order the im...

The Trade-Off between Directness and Coverage in Transport Network Growth arxiv.org/abs/2507.13005

Huge congrats 🙌🏻

Strength and weakness of disease-induced herd immunity in networks | PNAS When a fraction of a population becomes immune to an infectious disease, the population-wide infection risk decreases nonlinearly due to collective...

New paper in PNAS!🎉 doi.org/10.1073/pnas...

Is herd immunity to infectious diseases effective when induced by natural infection? Earlier studies have suggested that population heterogeneity makes disease-induced herd immunity more effective than previously thought. Our work challenges this notion.