Iskanje po katalogu digitalne knjižnice

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
Celotno besedilo (1,07 MB)
Gradivo ima več datotek! Več...

Opis: Understanding human behaviour in decision problems and strategicinteractions has wide-ranging applications in economics, psychology andartificial intelligence. Game theory offers a robust foundation for this under-standing, based on the idea that individuals aim to maximize a utilityfunction. However, the exact factors influencing strategy choices remainelusive. While traditional models try to explain human behaviour as a func-tion of the outcomes of available actions, recent experimental researchreveals that linguistic content significantly impacts decision-making, thusprompting a paradigm shift from outcome-based to language-based utilityfunctions. This shift is more urgent than ever, given the advancement ofgenerative AI, which has the potential to support humans in making criticaldecisions through language-based interactions. We propose sentiment analy-sis as a fundamental tool for this shift and take an initial step by analysing61 experimental instructions from the dictator game, an economic gamecapturing the balance between self-interest and the interest of others,which is at the core of many social interactions. Our meta-analysis showsthat sentiment analysis can explain human behaviour beyond economicoutcomes. We discuss future research directions. We hope this worksets the stage for a novel game-theoretical approach that emphasizes theimportance of language in human decisions.
Ključne besede: game theory, artificial intelligence, social preferences, language-based preferences, social physics, moral behavior, trust
Objavljeno v DKUM: 27.11.2024; Ogledov: 0; Prenosov: 4
Celotno besedilo (487,71 KB)
Gradivo ima več datotek! Več...

Opis: Evolutionary games provide the theoretical backbone for many aspects of our social life: from cooperation to crime, from climate inaction to imperfect vaccination and epidemic spreading, from antibiotics overuse to biodiversity preservation. An important, and so far overlooked, aspect of reality is the diverse strategic identities of individuals. While applying the same strategy to all interaction partners may be an acceptable assumption for simpler forms of life, this fails to account for the behavior of more complex living beings. For instance, we humans act differently around different people. Here we show that allowing individuals to adopt different strategies with different partners yields a very rich evolutionary dynamics, including time-dependent coexistence of cooperation and defection, systemwide shifts in the dominant strategy, and maturation in individual choices. Our results are robust to variations in network type and size, and strategy updating rules. Accounting for diverse strategic identities thus has far-reaching implications in the mathematical modeling of social games.
Ključne besede: cooperation, evolutionary game theory, social physics, collective dynamics, complex system
Objavljeno v DKUM: 20.11.2024; Ogledov: 0; Prenosov: 3
Celotno besedilo (4,71 MB)
Gradivo ima več datotek! Več...

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
Celotno besedilo (1,36 MB)
Gradivo ima več datotek! Več...

Opis: Networks form the backbone of many complex systems, ranging from the Internet to human societies. Accordingly, not only is the range of our interactions limited and thus best described and modeled by networks, it is also a fact that the networks that are an integral part of such models are often interdependent or even interconnected. Networks of networks or multilayer networks are therefore a more apt description of social systems. This colloquium is devoted to evolutionary games on multilayer networks, and in particular to the evolution of cooperation as one of the main pillars of modern human societies. We first give an overview of the most significant conceptual differences between single-layer and multilayer networks, and we provide basic definitions and a classification of the most commonly used terms. Subsequently, we review fascinating and counterintuitive evolutionary outcomes that emerge due to different types of interdependencies between otherwise independent populations. The focus is on coupling through the utilities of players, through the flow of information, as well as through the popularity of different strategies on different network layers. The colloquium highlights the importance of pattern formation and collective behavior for the promotion of cooperation under adverse conditions, as well as the synergies between network science and evolutionary game theory.
Ključne besede: kooperacija, sociološke mreže, evolucijske igre, kolektivni pojav, samo-organizacija, fazni prehodi, recipročnost, fizika socioloških sistemov, cooperation, social networks, evolutionary games, collective phenomena, self-organization, phase transitions, reciprocity, physics of social systems
Objavljeno v DKUM: 17.09.2024; Ogledov: 0; Prenosov: 1
Povezava na celotno besedilo