Artículos con la etiqueta ‘Social and Information Networks (cs.SI)’

Mental ability and common sense in an artificial society

Por • 27 mar, 2014 • Category: sociologia

We read newspapers and watch TV every day. There are many issues and many controversies. Since media are free, we can hear arguments from every possible side. How do we decide what is wrong or right? The first condition to accept a message is to understand it; messages that are too sophisticated are ignored. So it seems reasonable to assume that our understanding depends on our ability and our current knowledge. Here we show that the consequences of this statement are surprising and funny.

Fractal multi-level organisation of human groups in a virtual world

Por • 21 mar, 2014 • Category: sociologia

Humans are fundamentally social. They have progressively dominated their environment by the strength and creativity provided by and within their grouping. It is well recognised that human groups are highly structured, and the anthropological literature has loosely classified them according to their size and function, such as support cliques, sympathy groups, bands, cognitive groups, tribes, linguistic groups and so on. Recently, combining data on human grouping patterns in a comprehensive and systematic study, Zhou et al. identified a quantitative discrete hierarchy of group sizes with a preferred scaling ratio close to 3 , which was later confirmed for hunter-gatherer groups and for other mammalian societies. Using high precision large scale Internet-based social network data, we extend these early findings on a very large data set.

Selection rules in alliance formation: strategic decisions or abundance of choice?

Por • 15 mar, 2014 • Category: Economía

We study how firms select partners using a large database of publicly announced R&D alliances over a period of 25 years. We identify, for the first time, two distinct behavioral strategies of firms in forming these alliances. By reconstructing and analysing the temporal R&D network of 14,000 international firms and 21.000 publicly announced alliances, we find a “universal” behavior in firms changing between these strategies. In the first strategy, newcomers and nodes of low centrality initially establish links to nodes of similar or higher centrality.

The influence of persuasion in opinion formation and polarization

Por • 15 mar, 2014 • Category: Ambiente

We present a model that explores the influence of persuasion in a population of agents with positive and negative opinion orientations. The opinion of each agent is represented by an integer number k that expresses its level of agreement on a given issue, from totally against k=−M to totally in favor k=M . Same-orientation agents persuade each other with probability p , becoming more extreme, while opposite-orientation agents become more moderate as they reach a compromise with probability q .

Beyond network structure: How heterogenous susceptibility modulates the spread of epidemics

Por • 12 mar, 2014 • Category: Ciencia y tecnología

The compartmental models used to study epidemic spreading often assume the same susceptibility for all individuals, and are therefore, agnostic about the effects that differences in susceptibility can have on epidemic spreading. Here we show that–for the SIS model–differential susceptibility can make networks more vulnerable to the spread of diseases when the correlation between a node’s degree and susceptibility are positive, and less vulnerable when this correlation is negative. Moreover, we show that networks become more likely to contain a pocket of infection when individuals are more likely to connect with others that have similar susceptibility (the network is segregated).

Rich-cores in networks

Por • 20 feb, 2014 • Category: sociologia

The notion of a “rich-club” describes nodes which are essentially the hub of a network, as they play a dominating role in structural and functional properties. Interestingly, the definition of a rich-club naturally emphasizes high degree nodes and divides a network into two subgroups. Our approach theoretically couples the underlying principle of a rich-club with the escape time of a random walker, and a rich-core is defined by examining changes in the associated persistence probability. The method is fast and scalable to large networks. In particular, we successfully show that the evolution of the core in \emph{C. elegans} and World Trade networks correspond to key development stages and responses to historical events respectively.

Kantian fractionalization predicts the conflict propensity of the international system

Por • 8 feb, 2014 • Category: Política

The study of complex social and political phenomena with the perspective and methods of network science has proven fruitful in a variety of areas, including applications in political science and more narrowly the field of international relations. We propose a new line of research in the study of international conflict by showing that the multiplex fractionalization of the international system (which we label Kantian fractionalization) is a powerful predictor of the propensity for violent interstate conflict, a key indicator of the system’s stability. In so doing, we also demonstrate the first use of multislice modularity for community detection in a multiplex network application. Even after controlling for established system-level conflict indicators, we find that Kantian fractionalization contributes more to model fit for violent interstate conflict than previously established measures. Moreover, evaluating the influence of each of the constituent networks shows that joint democracy plays little, if any, role in predicting system stability, thus challenging a major empirical finding of the international relations literature.

Generalized friendship paradox in complex networks

Por • 15 ene, 2014 • Category: sociologia

The friendship paradox states that your friends have on average more friends than you have. Does the paradox “hold'” for other individual characteristics like income or happiness? To address this question, we generalize the friendship paradox for arbitrary node characteristics in complex networks.

Social Influences in the Voter Model: the Role of Conformity

Por • 7 ene, 2014 • Category: sociologia

We introduce a model to study the effects of social influences in opinion dynamics. In particular, we analyze the voter model, from a socio psychological perspective, by considering the role of conformity. Conformity is a central issue in social psychology as it represents one of people’s behaviors that emerge as result of their interactions. We introduce a voter model where agents, linked in a network, change their opinion according to those of their neighbors and to their degree of conformity. In particular, agents can behave as conformists or non-conformists. In the former case, agents change opinion according to that of the majority of their social circle (i.e., the majority of their neighbors); in the latter case, they do the opposite, i.e., they assume the opposite opinion. We perform a computational study of the proposed model, with the aim to analyze the role of conformity in the voter model. Moreover, we want to investigate whether it is possible to achieve some kind of equilibrium or of order in the system. The two more interesting results are that the amount of non-conformist agents in the population plays a central role in these dynamics, and the topology of the agent network has not a prominent role in the proposed model. Finally, we study the outcomes of the model by considering that agents can change also their degree of conformity over time, i.e., they can turn their behavior from conformist to non-conformist and vice-versa.

Analysis and Control of Beliefs in Social Networks

Por • 5 ene, 2014 • Category: sociologia

In this paper, we investigate the problem of how beliefs diffuse among members of social networks. We propose an information flow model (IFM) of belief that captures how interactions among members affect the diffusion and eventual convergence of a belief. The IFM model includes a generalized Markov Graph (GMG) model as a social network model, which reveals that the diffusion of beliefs depends heavily on two characteristics of the social network characteristics, namely degree centralities and clustering coefficients. We apply the IFM to both converged belief estimation and belief control strategy optimization. The model is compared with an IFM including the Barabasi-Albert model, and is evaluated via experiments with published real social network data.