1. Association between productivity and journal impact across disciplines and career ageAndre S. Sunahara, Matjaž Perc, Haroldo V. Ribeiro, 2021, izvirni znanstveni članek Opis: The association between productivity and impact of scientific production is a long-standing debate in science that remains controversial and poorly understood. Here we present a large-scale analysis of the association between yearly publication numbers and average journal-impact metrics for the Brazilian scientific elite. We find this association to be discipline specific, career age dependent, and similar among researchers with outlier and nonoutlier performance. Outlier researchers either outperform in productivity or journal prestige, but they rarely do so in both categories. Nonoutliers also follow this trend and display negative correlations between productivity and journal prestige but with discipline-dependent intensity. Our research indicates that academics are averse to simultaneous changes in their productivity and journal-prestige levels over consecutive career years. We also find that career patterns concerning productivity and journal prestige are discipline-specific, having in common a raise of productivity with career age for most disciplines and a higher chance of outperforming in journal impact during early career stages. Ključne besede: network, cooperation, social physics, complex system Objavljeno v DKUM: 10.12.2024; Ogledov: 0; Prenosov: 6
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2. Cross-sectional personal network analysis of adult smoking in rural areasBianca-Elena Mihǎilǎ, Marian-Gabriel Hâncean, Matjaž Perc, Jürgen Lerner, Iulian Oană, Marius Geanta, José Luis Molina González, Cosmina Cioroboiu, 2024, izvirni znanstveni članek Opis: Research on smoking behaviour has primarily focused on adolescents, with less attention given to middle-aged and older adults in rural settings. This study examines the influence of personal networks and sociodemographic factors on smoking behaviour in a rural Romanian community. We analysed data from 76 participants, collected through face-to-face interviews, including smoking status (non-smokers, current and former smokers), social ties and demographic details. Multilevel regression models were used to predict smoking status. The results indicate that social networks are essential in shaping smoking habits. Current smokers were more likely to have smoking family members, reinforcing smoking within familial networks, while non-smokers were typically embedded in non-smoking environments. Gender and age patterns show that women were less likely to smoke, and older adults were more likely to have quit smoking. These findings suggest that targeted interventions should focus not only on individuals but also on their social networks. In rural areas, family-based approaches may be particularly effective due to the strong influence of familial ties. Additionally, encouraging connections with non-smokers and former smokers could help disrupt smoking clusters, supporting smoking cessation efforts. Ključne besede: network science, human behaviour, data science, smoking, social physics Objavljeno v DKUM: 03.12.2024; Ogledov: 0; Prenosov: 0
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3. Assortative mixing of opinions about COVID‑19 vaccination in personal networksMarian-Gabriel Hâncean, Jürgen Lerner, Matjaž Perc, José Luis Molina González, Marius Geanta, 2024, izvirni znanstveni članek Opis: Many countries worldwide had difculties reaching a sufciently high vaccination uptake during the COVID-19 pandemic. Given this context, we collected data from a panel of 30,000 individuals, which were representative of the population of Romania (a country in Eastern Europe with a low 42.6% vaccination rate) to determine whether people are more likely to be connected to peers displaying similar opinions about COVID-19 vaccination. We extracted 443 personal networks, amounting to 4430 alters. We estimated multilevel logistic regression models with random-ego-level intercepts to predict individual opinions about COVID-19 vaccination. Our evidence indicates positive opinions about the COVID-19 vaccination cluster. Namely, the likelihood of having a positive opinion about COVID-19 vaccination increases when peers have, on average, a more positive attitude than the rest of the nodes in the network (OR 1.31, p < 0.001). We also found that individuals with higher education and age are more likely to hold a positive opinion about COVID-19 vaccination. With the given empirical data, our study cannot reveal whether this assortative mixing of opinions is due to social infuence or social selection. However, it may nevertheless have implications for public health interventions, especially in countries that strive to reach higher uptake rates. Understanding opinions about vaccination can act as an early warning system for potential outbreaks, inform predictions about vaccination uptake, or help supply chain management for vaccine distribution. Ključne besede: assortative mixing, opinions, vaccination, personal network, social physics Objavljeno v DKUM: 27.11.2024; Ogledov: 0; Prenosov: 0
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4. Socio-demographic and health factors drive the epidemic progression and should guide vaccination strategies for best COVID-19 containmentRene Markovič, Marko Šterk, Marko Marhl, Matjaž Perc, Marko Gosak, 2021, izvirni znanstveni članek Opis: We propose and study an epidemiological model on a social network that takes into account heterogeneity of the population and different vaccination strategies. In particular, we study how the COVID-19 epidemics evolves and how it is contained by different vaccination scenarios by taking into account data showing that older people, as well as individuals with comorbidities and poor metabolic health, and people coming from economically depressed areas with lower quality of life in general, are more likely to develop severe COVID-19 symptoms, and quicker loss of immunity and are therefore more prone to reinfection. Our results reveal that the structure and the spatial arrangement of subpopulations are important epidemiological determinants. In a healthier society the disease spreads more rapidly but the consequences are less disastrous as in a society with more prevalent chronic comorbidities. If individuals with poor health are segregated within one community, the epidemic outcome is less favorable. Moreover, we show that, contrary to currently widely adopted vaccination policies, prioritizing elderly and other higher-risk groups is beneficial only if the supply of vaccine is high. If, however, the vaccination availability is limited, and if the demographic distribution across the social network is homogeneous, better epidemic outcomes are achieved if healthy people are vaccinated first. Only when higher-risk groups are segregated, like in elderly homes, their prioritization will lead to lower COVID-19 related deaths. Accordingly, young and healthy individuals should view vaccine uptake as not only protecting them, but perhaps even more so protecting the more vulnerable socio-demographic groups. Ključne besede: epidemic model, COVID-19, vaccination strategy, vaccination strategy, population heterogeneity, socio-demographic structure, metabolic disease, social network Objavljeno v DKUM: 14.11.2024; Ogledov: 0; Prenosov: 9
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5. Multilayer representation of collaboration networks with higher-order interactionsE. Vasilyeva, A. Kozlov, Karin Alfaro-Bittner, D. Musatov, A. M. Raigorodskii, Matjaž Perc, Stefano Boccaletti, 2021, izvirni znanstveni članek Opis: Collaboration patterns offer important insights into how scientific breakthroughs and innovations emerge in small and large research groups. However, links in traditional networks account only for pairwise interactions, thus making the framework best suited for the description of two-person collaborations, but not for collaborations in larger groups. We therefore study higher-order scientific collaboration networks where a single link can connect more than two individuals, which is a natural description of collaborations entailing three or more people. We also consider different layers of these networks depending on the total number of collaborators, from one upwards. By doing so, we obtain novel microscopic insights into the representativeness of researchers within different teams and their links with others. In particular, we can follow the maturation process of the main topological features of collaboration networks, as we consider the sequence of graphs obtained by progressively merging collaborations from smaller to bigger sizes starting from the single-author ones. We also perform the same analysis by using publications instead of researchers as network nodes, obtaining qualitatively the same insights and thus confirming their robustness. We use data from the arXiv to obtain results specific to the fields of physics, mathematics, and computer science, as well as to the entire coverage of research fields in the database. Ključne besede: network, collaboration, social physics, complex system Objavljeno v DKUM: 18.10.2024; Ogledov: 0; Prenosov: 1
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6. Impact of social networks on the labor market inequalities and school-to-work transitionsMahmut Özer, Matjaž Perc, 2021, izvirni znanstveni članek Opis: Countries invest in education systems in order to increase the quality of their human capital. In this context, it is seen that especially after the expansion of the higher education systems, countries try to increase higher education graduation rates in order to improve the quality of human resources in the labor market. The ultimate goal of these efforts is to facilitate the transitions from school-to-work, and to increase social welfare by meeting the human resources needs of the labor market. The facilitation of school-to-work transitions has a direct impact on youth unemployment. School-to-work transitions are influenced not only by the quality of education from primary to higher education but also by the dynamics of the labor market. Social network analysis can provide important insights into this dynamics, and in doing so reveal that there are indeed many factors that play a key role in determining who gets a job and why, including, first and foremost, social contacts. An analysis of job search channels reveals that partners, friends, and relatives are those social contacts that are most decisive for employment outcomes. Research reveals that employers use social-contact-based reference channels much more frequently than formal channels for recruitment. Thus, employers frequently use such reference channels in recruitment. It has also been shown that the use of social-contact channels reduces employers' costs of finding suitable employees and increases productivity since employees hired through these channels also stay longer in their firms. We here explore the full potential of social network analysis to better our understanding of school-to-work transitions, to reveal in no uncertain terms the importance of social contacts, and to show how these insights can be leveraged to level the labor market for all involved. An important take-home message is that the labor market dynamics is strongly affected by the Matthew effect, such that the inequalities and the gaps between opportunities only grow and widen as the underlying social networks evolve. It is therefore important to mitigate these effects well before school-to-work transitions come into play, namely during the education. In particular, we assert that minimizing the inequalities during education should effectively mitigate the uneven impact of social networks on school-to-work transitions. Ključne besede: employment, higher education, inequality, labor market, Matthew effect, social network Objavljeno v DKUM: 04.10.2024; Ogledov: 0; Prenosov: 7
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7. Why are there six degrees of separation in a social network?I. Samoylenko, D. Aleja, E. Primo, Karin Alfaro-Bittner, E. Vasilyeva, K. Kovalenko, D. Musatov, A. M. Raigorodskii, R. Criado, M. Romance, David Papo, Matjaž Perc, B. Barzel, Stefano Boccaletti, 2023, izvirni znanstveni članek Opis: A wealth of evidence shows that real-world networks are endowed with the small-world property, i.e., that the maximal distance between any two of their nodes scales logarithmically rather than linearly with their size. In addition, most social networks are organized so that no individual is more than six connections apart from any other, an empirical regularity known as the six degrees of separation. Why social networks have this ultrasmall-world organization, whereby the graph’s diameter is independent of the network size over several orders of magnitude, is still unknown. We show that the “six degrees of separation” is the property featured by the equilibrium state of any network where individuals weigh between their aspiration to improve their centrality and the costs incurred in forming and maintaining connections. We show, moreover, that the emergence of such a regularity is compatible with all other features, such as clustering and scale-freeness, that normally characterize the structure of social networks. Thus, our results show how simple evolutionary rules of the kind traditionally associated with human cooperation and altruism can also account for the emergence of one of the most intriguing attributes of social networks. Ključne besede: degree distribution, network evolution, complex network, small-world network, social physics Objavljeno v DKUM: 16.07.2024; Ogledov: 111; Prenosov: 10
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8. Universality of political corruption networksAlvaro F. Martins, Bruno R. da Cunha, Quentin S. Hanley, Sebastián Gonçalves, Matjaž Perc, Haroldo V. Ribeiro, 2022, izvirni znanstveni članek Opis: Corruption crimes demand highly coordinated actions among criminal agents to succeed. But research dedicated to corruption networks is still in its infancy and indeed little is known about the properties of these networks. Here we present a comprehensive investigation of corruption networks related to political scandals in Spain and Brazil over nearly three decades. We show that corruption networks of both countries share universal structural and dynamical properties, including similar degree distributions, clustering and assortativity coefficients, modular structure, and a growth process that is marked by the coalescence of network components due to a few recidivist criminals. We propose a simple model that not only reproduces these empirical properties but reveals also that corruption networks operate near a critical recidivism rate below which the network is entirely fragmented and above which it is overly connected. Our research thus indicates that actions focused on decreasing corruption recidivism may substantially mitigate this type of organized crime. Ključne besede: corruption, network, politics, universality, social physics Objavljeno v DKUM: 15.07.2024; Ogledov: 119; Prenosov: 9
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9. Segregation dynamics driven by network leadersWen-Xuan Wang, Yuhao Feng, Siru Chen, Wenzhe Xu, Xinjian Zhuo, Huijia Li, Matjaž Perc, 2022, izvirni znanstveni članek Opis: Network segregation - a critical problem in real-life networks - can reveal the emergence of conflicts or signal an impending collapse of the whole system. However, the strong heterogeneity of such networks and the various definitions for key nodes continue to pose challenges that limit our ability to foresee segregation and to determine the main drivers behind it. In this paper, we show that a multi-agent leader-follower consensus system can be utilized to define a new index, named leadership, to identify key leaders in real-life networks. And then, this paper explores the emergence of network segregation that is driven by these leaders based on the removal or the rewiring of the relations between different nodes in agreement with their contribution distance. We finally show that the observed leaders-driven segregation dynamics reveals the dynamics of heterogeneous attributes that critically influence network structure and its segregation. Thus, this paper provides a theoretical method to study complex social interactions and their roles in network segregation, which ultimately leads to a closed-form explanation for the emergence of imbalanced network structure from an evolutionary perspective. Ključne besede: complex networks, network segregation, multi-agent leader–follower consensus system, key leaders identification, leader, segregation, social physics Objavljeno v DKUM: 08.07.2024; Ogledov: 122; Prenosov: 13
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10. Epidemic trajectories and awareness diffusion among unequals in simplicial complexesLijin Liu, Meiling Feng, Chengyi Xia, Dawei Zhao, Matjaž Perc, 2023, izvirni znanstveni članek Opis: The interplay between awareness diffusion and epidemic spreading has been an active topic of research in recent years. Studies have shown that group interactions are an important consideration in contagion processes, and that thus higher-order interactions should be introduced into epidemic modeling. Research has also shown that individual responses to an unfolding epidemic are often strongly heterogeneous. We therefore present a two-layer network model, where the diffusion of awareness unfolds over 2-simplicial complexes in one layer, and the actual epidemic spreading unfolds over pairwise physical contacts in the other layer. The model takes into account individual differences in the degree of acceptance of information and self-protection measures once the epidemic is perceived. We use the micro Markov chain approach to determine the epidemic threshold of the model, which agrees well with the results obtained by Monte Carlo simulations. We show that the synergistic reinforcement due to 2-simplicial complexes in the virtual layer can restrain epidemic spreading by facilitating awareness diffusion, and moreover, that individual heterogeneity in the physical layer can increase the epidemic threshold and decrease the size of epidemic transmission. However, heterogeneity in the perception can also have the opposite effect because it inhibits the diffusion of awareness. Our results reveal the intricate interplay between awareness diffusion and epidemic spreading, and we hope they can help determine effective control measures. Ključne besede: higher-order interactions, awareness diffusion, epidemic spreading, multiplex network, social physics Objavljeno v DKUM: 21.06.2024; Ogledov: 163; Prenosov: 17
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