The innovation trade-off: how following superstars shapes academic novelty

Sean Kelty, Raiyan Abdul Baten, Adiba Mahbub Proma, Ehsan Hoque, Johan Bollen & Gourab Ghoshal
Humanities and Social Sciences Communications volume 12, Article number: 926 (2025)

Academic success is distributed unequally; a few top scientists receive the bulk of attention, citations, and resources. However, do these “superstars” foster leadership in scientific innovation? We employ a series of information-theoretic measures that quantify novelty, innovation, and impact from scholarly citation networks, and compare the academic output of scientists in the American Physical Society corpus with varying levels of connections to superstar scientists. The strength of connection is based on the frequency of citations to superstar papers, which is also related to the frequency of collaboration. We find that while strongly-connected scientists publish more, garner more citations, and produce moderately more diverse content, this comes at a cost of lower innovation, less disruption, and higher redundancy of ideas. Further, once one removes papers co-authored with superstars, the academic output of these strongly connected scientists greatly diminishes. In contrast, authors who publish at the same rate without the benefit of collaborations with scientific superstars produce papers that are more innovative, more disruptive, and have comparable citation rates, once one controls for the transferred prestige of superstars. On balance, our results indicate that academia pays a price by focusing attention and resources on superstars.

Read the full article at: www.nature.com

Life Finds A Way: Emergence of Cooperative Structures in Adaptive Threshold Networks

Sean P. Maley, Carlos Gershenson, Stuart A. Kauffman

There has been a long debate on how new levels of organization have evolved. It might seem unlikely, as cooperation must prevail over competition. One well-studied example is the emergence of autocatalytic sets, which seem to be a prerequisite for the evolution of life. Using a simple model, we investigate how varying bias toward cooperation versus antagonism shapes network dynamics, revealing that higher-order organization emerges even amid pervasive antagonistic interactions. In general, we observe that a quantitative increase in the number of elements in a system leads to a qualitative transition.
We present a random threshold-directed network model that integrates node-specific traits with dynamic edge formation and node removal, simulating arbitrary levels of cooperation and competition. In our framework, intrinsic node values determine directed links through various threshold rules. Our model generates a multi-digraph with signed edges (reflecting support/antagonism, labeled “help”/“harm”), which ultimately yields two parallel yet interdependent threshold graphs. Incorporating temporal growth and node turnover in our approach allows exploration of the evolution, adaptation, and potential collapse of communities and reveals phase transitions in both connectivity and resilience.
Our findings extend classical random threshold and Erdős-Rényi models, offering new insights into adaptive systems in biological and economic contexts, with emphasis on the application to Collective Affordance Sets. This framework should also be useful for making predictions that will be tested by ongoing experiments of microbial communities in soil.

Read the full article at: arxiv.org

Tendencies toward triadic closure: Field experimental evidence

Mohsen Mosleh,, Dean Eckles, and David G. Rand
PNAS 122 (27) e2404590122
Empirical social networks are characterized by a high degree of triadic closure (i.e., transitivity, clustering): network neighbors of the same individual are also likely to be directly connected. It is unknown to what degree this results from dispositions to form such ties (i.e., to close open triangles) per se versus other processes such as homophily and more opportunities for exposure. These mechanisms are difficult to disentangle in many settings. On social media, however, they can be decomposed – and platforms frequently make decisions that depend on these distinct processes. Here, using a field experiment on social media, we randomize the existing network structure that a user faces when they are followed by a target account that we control. We then examine whether the user reciprocates this tie formation. Being randomly assigned to have an existing tie to an account that follows the target user increases tie formation by 35%. Through multiple control conditions, we attribute this effect specifically to a minimal cue that indicates the presence of a potential mutual follower. Theory suggests that triadic closure should be especially likely in open triads of strong ties, and accordingly we find larger effects when the subject has interacted more with the existing follower. These results indicate a substantial role for tendencies toward triadic closure, but one that is substantially smaller than what might be inferred from prior observational studies. Platforms and others may rely on these tendencies in encouraging tie formation, with broader implications for network structure and information diffusion in online networks

Read the full article at: www.pnas.org

Applied Antifragility in Natural Systems: From Principles to Applications

Cristian Axenie , Roman Bauer , Oliver López Corona , Jeffrey West

As coined in the book of Nassim Taleb, antifragility is a property of a system to gain from uncertainty, randomness, and volatility, opposite to what fragility would incur. An antifragile system’s response to external perturbations is beyond robust, such that small stressors can strengthen the future response of the system by adding a strong anticipation component. Such principles are already well suited for describing behaviors in natural systems but also in approaching therapy designs and eco-system modelling and eco-system analysis.

The purpose of this book is to build a foundational knowledge base by applying antifragile system design, analysis, and development in natural systems, including biomedicine, neuroscience, and ecology as main fields. We are interested in formalizing principles and an apparatus that turns the basic concept of antifragility into a tool for designing and building closed-loop systems that behave beyond robust in the face of uncertainty when characterizing and intervening in biomedical and ecological (eco)systems.

The book introduces the framework of applied antifragility and possible paths to build systems that gain from uncertainty. We draw from the body of literature on natural systems (e.g. cancer therapy, antibiotics, neuroscience, and agricultural pest management) in an attempt to unify the scales of antifragility in one framework. The work of the Applied Antifragility Group in oncology, neuroscience, and ecology led by the authors provides a good overview on the current research status.

Read the full article at: link.springer.com

Applied Antifragility in Technical Systems: From Principles to Applications

Cristian Axenie , Meisam Akbarzadeh , Michail A. Makridis , Matteo Saveriano , Alexandru Stancu

The book purpose is to build a foundational knowledge base by applying antifragile system design, analysis, and development in technical systems, with a focus on traffic engineering, robotics, and control engineering. The authors are interested in formalizing principles and an apparatus that turns the basic concept of antifragility into a tool for designing and building closed-loop technical systems that behave beyond robust in the face of uncertainty.

As coined in the book of Nassim Taleb, antifragility is a property of a system to gain from uncertainty, randomness, and volatility, opposite to what fragility would incur. An antifragile system’s response to external perturbations is beyond robust, such that small stressors can strengthen the future response of the system by adding a strong anticipation component. The work of the Applied Antifragility Group in traffic control and robotics, led by the authors, provides a good overview on the current research status.

Read the full article at: link.springer.com