Irrational herding persists in human-bot interactions Luca Verginer, Giacomo Vaccario, Piero Ronzani Scientific Reports, 2025 We explore human herding in a strategic setting where humans interact with automated entities (bots) and study the shift in the behaviour and beliefs of humans when they are aware of interacting with bots. The strategic setting is an online minority game, where 1997 participants are rewarded for following the minority strategy. This setting permits distinguishing between irrational herding and rational self-interest—a fundamental challenge in understanding herding in strategic contexts. Moreover, participants were divided into two groups: one informed of playing against bots (informed condition) and the other unaware (not-informed condition). Our findings revealed that while informed participants adjusted their beliefs about bots’ behaviour, their actual decisions remained largely unaffected. In both conditions, 30% of participants followed the majority, contrary to theoretical expectations of no herding. This study underscores the persistence of herding behaviour in human decision-making, even when participants are aware of interacting with automated entities. The insights provide profound implications for understanding human behaviour on digital platforms where interactions with bots are common.
Coexistence of balance and hierarchies: An ego perspective to explain empirical networks Piotr J Górski, Adam Sulik, Georges Andres, Giacomo Vaccario, Janusz A Hołyst Pnas Nexus, 2025 The formation of positive and negative relations between individuals in social networks can be described by different approaches. Two prominent mechanisms are structural balance and status hierarchies. Balance motivates stability among friends and enemies in triads (e.g. an enemy of my friend is my enemy). Status considers respect and disregard originating from social hierarchy (e.g. positive relations towards those we respect). We demonstrate that integrating the two mechanisms through the concept of ego dynamics is key to understanding observable patterns in many social groups. We propose an agent-based model where dynamical changes result from agents aiming to resolve inconsistencies with structural balance and status. In contrast to previous models, our approach employs the ego perspective. Agents have limited, local knowledge and can only change their own relations. By fitting the model to real-world networks, we successfully replicated the observed over- and under-representations of certain triads in 36 empirical signed networks. This close matching to empirical data is achievable only by taking the ego perspective and not assuming global knowledge. Additionally, the model reveals that, when the status mechanism dominates, people in real networks tend to strive for the top of the hierarchy. Finally, our numerical simulations and analytic solutions demonstrate that a previously thought as continuous phase transition towards the paradise state (all links positive) can become discontinuous when the status mechanism is involved. This discontinuity indicates that desirable social configurations may, in fact, be quite fragile.
Efficiency and resilience: key drivers of distribution network growth Ambra Amico, Giacomo Vaccario, Frank Schweitzer EPJ Data Science, 2024 Networks to distribute goods, from raw materials to food and medicines, are the backbone of a functioning economy. They are shaped by several supply relations connecting manufacturers, distributors, and final buyers worldwide. We present a network-based model to describe the mechanisms underlying the emergence and growth of distribution networks. In our model, firms consider two practices when establishing new supply relations: centralization, the tendency to choose highly connected partners, and multi-sourcing, the preference for multiple suppliers. Centralization enhances network efficiency by leveraging short distribution paths; multi-sourcing fosters resilience by providing multiple distribution paths connecting final buyers to the manufacturer. We validate the proposed model using data on drug shipments in the US. Drawing on these data, we reconstruct 22 nationwide pharmaceutical distribution networks. We demonstrate that the proposed model successfully replicates several structural features of the empirical networks, including their out-degree and path length distributions as well as their resilience and efficiency properties. These findings suggest that the proposed firm-level practices effectively capture the network growth process that leads to the observed structures.
Adapting to disruptions: Managing supply chain resilience through product rerouting Ambra Amico, Luca Verginer, Giona Casiraghi, Giacomo Vaccario, Frank Schweitzer Science Advances, 2024 Supply chain disruptions may cause shortages of essential goods, affecting millions of individuals. We propose a perspective to address this problem via reroute flexibility. This is the ability to substitute and reroute products along existing pathways, hence without requiring the creation of new connections. To showcase the potential of this approach, we examine the US opioid distribution system. We reconstruct over 40 billion distribution routes and quantify the effectiveness of reroute flexibility in mitigating shortages. We demonstrate that flexibility (i) reduces the severity of shortages and (ii) delays the time until they become critical. Moreover, our findings reveal that while increased flexibility alleviates shortages, it comes at the cost of increased complexity: We demonstrate that reroute flexibility increases alternative path usage and slows down the distribution system. Our method enhances decision-makers’ ability to manage the resilience of supply chains.
Reconstructing signed relations from interaction data Georges Andres, Giona Casiraghi, Giacomo Vaccario, Frank Schweitzer Scientific Reports, 2023 Positive and negative relations play an essential role in human behavior and shape the communities we live in. Despite their importance, data about signed relations is rare and commonly gathered through surveys. Interaction data is more abundant, for instance, in the form of proximity or communication data. So far, though, it could not be utilized to detect signed relations. In this paper, we show how the underlying signed relations can be extracted with such data. Employing a statistical network approach, we construct networks of signed relations in five communities. We then show that these relations correspond to the ones reported by the individuals themselves. Additionally, using inferred relations, we study the homophily of individuals with respect to gender, religious beliefs, and financial backgrounds. Finally, we study group cohesion in the analyzed communities by evaluating triad statistics in the reconstructed signed network.
MODELING SOCIAL RESILIENCE: QUESTIONS, ANSWERS, OPEN PROBLEMS FRANK SCHWEITZER, GEORGES ANDRES, GIONA CASIRAGHI, CHRISTOPH GOTE, RAMONA ROLLER, et al. Advances in Complex Systems, 2022 Resilience denotes the capacity of a system to withstand shocks and its ability to recover from them. We develop a framework to quantify the resilience of highly volatile, non-equilibrium social organizations, such as collectives or collaborating teams. It consists of four steps: (i) delimitation, i.e. narrowing down the target systems, (ii) conceptualization, i.e. identifying how to approach social organizations, (iii) formal representation using a combination of agent-based and network models, (iv) operationalization, i.e. specifying measures and demonstrating how they enter the calculation of resilience. Our framework quantifies two dimensions of resilience, the robustness of social organizations and their adaptivity, and combines them in a novel resilience measure. It allows monitoring resilience instantaneously using longitudinal data instead of an ex-post evaluation.
The role of network embeddedness on the selection of collaboration partners: An agent-based model with empirical validation FRANK SCHWEITZER, ANTONIOS GARAS, MARIO V. TOMASELLO, GIACOMO VACCARIO, LUCA VERGINER Agents Networks Evolution A Quarter Century of Advances in Complex Systems, 2022 We use a data-driven agent-based model to study the core–periphery structure of two collaboration networks, R&D alliances between firms and co-authorship relations between scientists. To characterize the network embeddedness of agents, we introduce a coreness value obtained from a weighted [Formula: see text]-core decomposition. We study the change of these coreness values when collaborations with newcomers or established agents are formed. Our agent-based model is able to reproduce the empirical coreness differences of collaboration partners and to explain why we observe a change in partner selection for agents with high network embeddedness.
Structurally balanced growing network as randomized P\'olya urn process K Mohandas, PJ Górski, K Suchecki, G Andres, G Vaccario, JA Hołyst arXiv preprint arXiv:2510.24659 , 2025 2025 Citations: 2
Irrational herding persists in human-bot interactions L Verginer, G Vaccario, P Ronzani Scientific Reports 15 (1), 22828 , 2025 2025 Citations: 3
Coexistence of balance and hierarchies: An ego perspective to explain empirical networks PJ Górski, A Sulik, G Andres, G Vaccario, JA Hołyst PNAS nexus 4 (5), pgaf130 , 2025 2025 Citations: 1
Efficiency and resilience: key drivers of distribution network growth A Amico, G Vaccario, F Schweitzer EPJ Data Science 13 (1), 52 , 2024 2024 Citations: 6
The quest for an unbiased scientific impact indicator remains open G Vaccario, S Xu, MS Mariani, M Medo Proceedings of the National Academy of Sciences 121 (41), e2410021121 , 2024 2024 Citations: 4
Adapting to disruptions: Managing supply chain resilience through product rerouting A Amico, L Verginer, G Casiraghi, G Vaccario, F Schweitzer Science Advances 10 (3), eadj1194 , 2024 2024 Citations: 30
Reconstructing signed relations from interaction data G Andres, G Casiraghi, G Vaccario, F Schweitzer Scientific Reports 13 (1), 20689 , 2023 2023 Citations: 11
Fragmentation from group interactions: A higher-order adaptive voter model N Papanikolaou, R Lambiotte, G Vaccario Physica A: Statistical Mechanics and its Applications 630, 129257 , 2023 2023 Citations: 4
Modeling the Impact of Environmental Consciousness on the Supply-Demand Relationship between Firms and Customers T Wang, G Vaccario, F Schweitzer Available at SSRN 4403242 , 2023 2023
Modeling social resilience: Questions, answers, open problems F Schweitzer, G Andres, G Casiraghi, C Gote, R Roller, I Scholtes, ... Advances in Complex Systems 25 (08), 2250014 , 2022 2022 Citations: 22
When standard network measures fail to rank journals: A theoretical and empirical analysis G Vaccario, L Verginer Quantitative Science Studies 3 (4), 1040-1053 , 2022 2022
Network embeddedness indicates the innovation potential of firms G Vaccario, L Verginer, A Garas, MV Tomasello, F Schweitzer arXiv preprint arXiv:2205.07677 , 2022 2022 Citations: 2
Consensus from group interactions: An adaptive voter model on hypergraphs N Papanikolaou, G Vaccario, E Hormann, R Lambiotte, F Schweitzer Physical Review E 105 (5), 054307 , 2022 2022 Citations: 44
The role of network embeddedness on the selection of collaboration partners: An agent-based model with empirical validation F Schweitzer, A Garas, MV Tomasello, G Vaccario, L Verginer Advances in Complex Systems, 2022, 2250003 , 2022 2022 Citations: 6
Foreword to the special issue on success in science L Verginer, G Vaccario, AM Petersen Advances in Complex Systems 24 (03n04), 2102001 , 2021 2021 Citations: 1
Reproducing scientists’ mobility: A data-driven model G Vaccario, L Verginer, F Schweitzer Scientific reports 11 (1), 1-11 , 2021 2021 Citations: 31
The mobility network of scientists: Analyzing temporal correlations in scientific careers G Vaccario, L Verginer, F Schweitzer Applied Network Science 5 (1), 36 , 2020 2020 Citations: 38
Should the government reward cooperation? Insights from an agent-based model of wealth redistribution F Schweitzer, L Verginer, G Vaccario Advances in Complex Systems , 2020 2020 Citations: 1
What is the Entropy of a Social Organization? C Zingg, G Casiraghi, G Vaccario, F Schweitzer Entropy 21 (9), 901 , 2019 2019 Citations: 24
The structure, exchange, and transfer of knowledge in socio-technical systems G Vaccario ETH Zurich , 2019 2019
MOST CITED SCHOLAR PUBLICATIONS
First-Passage Times in d-Dimensional Heterogeneous Media G Vaccario, C Antoine, J Talbot Physical Review Letters 115 (24), 240601 , 2015 2015.0 Citations: 63
Quantifying and suppressing ranking bias in a large citation network G Vaccario, M Medo, N Wider, MS Mariani Journal of Informetrics 11 (3), 766-782 , 2017 2017.0 Citations: 53
Consensus from group interactions: An adaptive voter model on hypergraphs N Papanikolaou, G Vaccario, E Hormann, R Lambiotte, F Schweitzer Physical Review E 105 (5), 054307 , 2022 2022.0 Citations: 44
The mobility network of scientists: Analyzing temporal correlations in scientific careers G Vaccario, L Verginer, F Schweitzer Applied Network Science 5 (1), 36 , 2020 2020.0 Citations: 38
Reproducing scientists’ mobility: A data-driven model G Vaccario, L Verginer, F Schweitzer Scientific reports 11 (1), 1-11 , 2021 2021.0 Citations: 31
Adapting to disruptions: Managing supply chain resilience through product rerouting A Amico, L Verginer, G Casiraghi, G Vaccario, F Schweitzer Science Advances 10 (3), eadj1194 , 2024 2024.0 Citations: 30
Data-driven modeling of collaboration networks: a cross-domain analysis MV Tomasello, G Vaccario, F Schweitzer EPJ Data Science 6 (1), 22 , 2017 2017.0 Citations: 26
What is the Entropy of a Social Organization? C Zingg, G Casiraghi, G Vaccario, F Schweitzer Entropy 21 (9), 901 , 2019 2019.0 Citations: 24
Modeling social resilience: Questions, answers, open problems F Schweitzer, G Andres, G Casiraghi, C Gote, R Roller, I Scholtes, ... Advances in Complex Systems 25 (08), 2250014 , 2022 2022.0 Citations: 22
Quantifying knowledge exchange in R&D networks: A data-driven model G Vaccario, MV Tomasello, CJ Tessone, F Schweitzer Journal of Evolutionary Economics 28 (3), 461–493 , 2017 2017.0 Citations: 19
Reconstructing signed relations from interaction data G Andres, G Casiraghi, G Vaccario, F Schweitzer Scientific Reports 13 (1), 20689 , 2023 2023.0 Citations: 11
The mobility network of scientists: analyzing temporal correlations in scientific careers. Applied Network Science. 2020; 5: 36 G Vaccario, L Verginer, F Schweitzer Citations: 7
Efficiency and resilience: key drivers of distribution network growth A Amico, G Vaccario, F Schweitzer EPJ Data Science 13 (1), 52 , 2024 2024.0 Citations: 6
The role of network embeddedness on the selection of collaboration partners: An agent-based model with empirical validation F Schweitzer, A Garas, MV Tomasello, G Vaccario, L Verginer Advances in Complex Systems, 2022, 2250003 , 2022 2022.0 Citations: 6
The quest for an unbiased scientific impact indicator remains open G Vaccario, S Xu, MS Mariani, M Medo Proceedings of the National Academy of Sciences 121 (41), e2410021121 , 2024 2024.0 Citations: 4
Fragmentation from group interactions: A higher-order adaptive voter model N Papanikolaou, R Lambiotte, G Vaccario Physica A: Statistical Mechanics and its Applications 630, 129257 , 2023 2023.0 Citations: 4
Irrational herding persists in human-bot interactions L Verginer, G Vaccario, P Ronzani Scientific Reports 15 (1), 22828 , 2025 2025.0 Citations: 3
Structurally balanced growing network as randomized P\'olya urn process K Mohandas, PJ Górski, K Suchecki, G Andres, G Vaccario, JA Hołyst arXiv preprint arXiv:2510.24659 , 2025 2025.0 Citations: 2
Network embeddedness indicates the innovation potential of firms G Vaccario, L Verginer, A Garas, MV Tomasello, F Schweitzer arXiv preprint arXiv:2205.07677 , 2022 2022.0 Citations: 2
Coexistence of balance and hierarchies: An ego perspective to explain empirical networks PJ Górski, A Sulik, G Andres, G Vaccario, JA Hołyst PNAS nexus 4 (5), pgaf130 , 2025 2025.0 Citations: 1
