arXiv subjects

K. Sneppen

Publications and source records attributed to K. Sneppen.

At least 19 recordsLinked to original sources

arXiv2009

Reinforced communication and social navigation generate groups in model networks

To investigate the role of information flow in group formation, we introduce a model of communication and social navigation. We let agents gather information in an idealized network society, and demonstrate that heterogeneous groups can evolve without presuming that individuals have different interests. In our scenario, individuals' access to global information is constrained by local communication with the nearest neighbors on a dynamic network. The result is reinforced interests among like-minded agents in modular networks; the flow of information works as a glue that keeps individuals together. The model explains group formation in terms of limited information access and highlights global broadcasting of information as a way to counterbalance this fragmentation. To illustrate how the information constraints imposed by the communication structure affects future development of real-world systems, we extrapolate dynamics from the topology of four social networks.

physics.soc-ph↗

arXiv2007

Dynamics of Opinions and Social Structures

Social groups with widely different music tastes, political convictions, and religious beliefs emerge and disappear on scales from extreme subcultures to mainstream mass-cultures. Both the underlying social structure and the formation of opinions are dynamic and changes in one affect the other. Several positive feedback mechanisms have been proposed to drive the diversity in social and economic systems, but little effort has been devoted to pinpoint the interplay between a dynamically changing social network and the spread and gathering of information on the network. Here we analyze this phenomenon in terms of a social network-model that explicitly simulates the feedback between information assembly and emergence of social structures: changing beliefs are coupled to changing relationships because agents self-organize a dynamic network to facilitate their hunter-gatherer behavior in information space. Our analysis demonstrates that tribal organizations and modular social networks can emerge as a result of contact-seeking agents that reinforce their beliefs among like-minded. We also find that prestigious persons can streamline the social network into hierarchical structures around themselves.

physics.soc-ph↗

arXiv2007

Oscillations and temporal signalling in cells

The development of new techniques to quantitatively measure gene expression in cells has shed light on a number of systems that display oscillations in protein concentration. Here we review the different mechanisms which can produce oscillations in gene expression or protein concentration, using a framework of simple mathematical models. We focus on three eukaryotic genetic regulatory networks which show "ultradian" oscillations, with time period of the order of hours, and involve, respectively, proteins important for development (Hes1), apoptosis (p53) and immune response (NFkB). We argue that underlying all three is a common design consisting of a negative feedback loop with time delay which is responsible for the oscillatory behaviour.

q-bio.MN↗

arXiv2006

Networks and Our Limited Information Horizon

In this paper we quantify our limited information horizon, by measuring the information necessary to locate specific nodes in a network. To investigate different ways to overcome this horizon, and the interplay between communication and topology in social networks, we let agents communicate in a model society. Thereby they build a perception of the network that they can use to create strategic links to improve their standing in the network. We observe a narrow distribution of links when the communication is low and a network with a broad distribution of links when the communication is high.

cond-mat.dis-nn↗

arXiv2006

Self-Assembly of Information in Networks

We model self-assembly of information in networks to investigate necessary conditions for building a global perception of a system by local communication. Our approach is to let agents chat in a model system to self-organize distant communication-pathways. We demonstrate that simple local rules allow agents to build a perception of the system, that is robust to dynamical changes and mistakes. We find that messages are most effectively forwarded in the presence of hubs, while transmission in hub-free networks is more robust against misinformation and failures.

physics.soc-ph↗

arXiv2005

Modeling self-organization of communication and topology in social networks

This paper introduces a model of self-organization between communication and topology in social networks, with a feedback between different communication habits and the topology. To study this feedback, we let agents communicate to build a perception of a network and use this information to create strategic links. We observe a narrow distribution of links when the communication is low and a system with a broad distribution of links when the communication is high. We also analyze the outcome of chatting, cheating, and lying, as strategies to get better access to information in the network. Chatting, although only adopted by a few agents, gives a global gain in the system. Contrary, a global loss is inevitable in a system with too many liars

physics.soc-ph↗

arXiv2005

Navigating Networks with Limited Information

We study navigation with limited information in networks and demonstrate that many real-world networks have a structure which can be described as favoring communication at short distance at the cost of constraining communication at long distance. This feature, which is robust and more evident with limited than with complete information, reflects both topological and possibly functional design characteristics. For example, the characteristics of the networks studied derived from a city and from the Internet are manifested through modular network designs. We also observe that directed navigation in typical networks requires remarkably little information on the level of individual nodes. By studying navigation, or specific signaling, we take a complementary approach to the common studies of information transfer devoted to broadcasting of information in studies of virus spreading and the like.

cond-mat.dis-nn↗

arXiv2005

Searchability of Networks

We investigate the searchability of complex systems in terms of their interconnectedness. Associating searchability with the number and size of branch points along the paths between the nodes, we find that scale-free networks are relatively difficult to search, and thus that the abundance of scale-free networks in nature and society may reflect an attempt to protect local areas in a highly interconnected network from nonrelated communication. In fact, starting from a random node, real-world networks with higher order organization like modular or hierarchical structure are even more difficult to navigate than random scale-free networks. The searchability at the node level opens the possibility for a generalized hierarchy measure that captures both the hierarchy in the usual terms of trees as in military structures, and the intrinsic hierarchical nature of topological hierarchies for scale-free networks as in the Internet.

cond-mat.dis-nn↗

arXiv2005

Networks and Cities: An Information Perspective

Traffic is constrained by the information involved in locating the receiver and the physical distance between sender and receiver. We here focus on the former, and investigate traffic in the perspective of information handling. We re-plot the road map of cities in terms of the information needed to locate specific addresses and create information city networks with roads mapped to nodes and intersections to links between nodes. These networks have the broad degree distribution found in many other complex networks. The mapping to an information city network makes it possible to quantify the information associated with locating specific addresses.

cond-mat.dis-nn↗

arXiv2004

Information Horizons in Networks

We investigate and quantify the interplay between topology and ability to send specific signals in complex networks. We find that in a majority of investigated real-world networks the ability to communicate is favored by the network topology on small distances, but disfavored at larger distances. We further discuss how the ability to locate specific nodes can be improved if information associated to the overall traffic in the network is available.

cond-mat.dis-nn↗

arXiv2004

Need, Greed and Noise: Competing Strategies in a Trading Model

We study an economic model where agents trade a variety of products by using one of three competing rules: "need", "greed" and "noise". We find that the optimal strategy for any agent depends on both product composition in the overall market and composition of strategies in the market. In particular, a strategy that does best on pairwise competition may easily do much worse when all are present, leading, in some cases, to a "paper, stone, scissors" circular hierarchy.

cond-mat.other↗

arXiv2004

Hide and seek on complex networks

Signaling pathways and networks determine the ability to communicate in systems ranging from living cells to human society. We investigate how the network structure constrains communication in social-, man-made and biological networks. We find that human networks of governance and collaboration are predictable on teat-a-teat level, reflecting well defined pathways, but globally inefficient. In contrast, the Internet tends to have better overall communication abilities, more alternative pathways, and is therefore more robust. Between these extremes the molecular network of Saccharomyces cerevisea is more similar to the simpler social systems, whereas the pattern of interactions in the more complex Drosophilia melanogaster, resembles the robust Internet.

cond-mat.dis-nn↗

arXiv2004

Self-organization of structures and networks from merging and small-scale fluctuations

We discuss merging-and-creation as a self-organizing process for scale-free topologies in networks. Three power-law classes characterized by the power-law exponents 3/2, 2 and 5/2 are identified and the process is generalized to networks. In the network context the merging can be viewed as a consequence of optimization related to more efficient signaling.

cond-mat.dis-nn↗

arXiv2003

Cooperativity in a trading model with memory and production

We consider in a market model the cooperative emergence of value due to a positive feedback between perception of needs and demand. Here we consider also a negative feedback from production of the traded products, and find that this cooperativity is robust, provided that the production rate is slow. Cooperativity is found to be critically linked to the ability to minimize the overall need, and thus disappears when the agents are poor, when the production rate is large or when there is little trade. We further observe that a cooperative economy may self-organize to compensate for an eventual slow production rate of certain products, so that these products are found in sizeable stocks. This differs qualitatively from an economy where cooperativity did not develop, in which case no product has a stock larger than what its bare production rate justifies. We also find that these results are robust in relation to the spatial restriction of the agents.

cond-mat.soft↗

arXiv2003

Scaling in Fracture and Refreezing of Sea Ice

Sea ice breaks up and regenerates rapidly during winter conditions in the Arctic. Analyzing satellite data from the Kara Sea, we find that the average ice floe size depends on weather conditions. Nevertheless, the frequency of floes of size $A$ is a power law, $N\sim A^{-τ}$, where $τ=1.6\pm 0.2$, for $A$ less than approximately 100 $km^2$. This scale-invariant behaviour suggests a competition between fracture due to strains in the ice field and refreezing of the fractures. A cellular model for this process gives results consistent with observations.

cond-mat.stat-mech↗

arXiv2002

Time delay as a key to Apoptosis Induction in the p53 Network

A feedback mechanism that involves the proteins p53 and mdm2, induces cell death as a controled response to severe DNA damage. A minimal model for this mechanism demonstrates that the respone may be dynamic and connected with the time needed to translate the mdm2 protein. The response takes place if the dissociation constant k between p53 and mdm2 varies from its normal value. Although it is widely believed that it is an increase in k that triggers the response, we show that the experimental behaviour is better described by a decrease in the dissociation constant. The response is quite robust upon changes in the parameters of the system, as required by any control mechanism, except for few weak points, which could be connected with the onset of cancer.

cond-mat.dis-nn↗

arXiv2001

Epigenetics as a first exit problem

We develop a framework to discuss stability of epigenetic states as first exit problems in dynamical systems with noise. We consider in particular the stability of the lysogenic state of the lambda prophage, which is known to exhibit exceptionally large stability. The formalism defines a quantative measure of robustness of inherited states. In contrast to Kramers' well-known problem of escape from a potential well, the stability of inherited states in our formulation is not a numerically trivial problem. The most likely exit path does not go along a steepest decent of a potential -- there is no potential. Instead, such a path can be described as a zero-energy trajectory between two equilibria in an auxiliary classical mechanical system. Finding it is similar to e.g. computing heteroclinic orbits in celestial mechanics. The overall lesson of this study is that an examination of equilibria and their bifurcations with changing parameter values allow us to quantify both the stability and the robustness of particular states of a genetic control system.

cond-mat.soft↗

arXiv2000

Self-organization of value and demand

We study the dynamics of exchange value in a system composed of many interacting agents. The simple model we propose exhibits cooperative emergence and collapse of global value for individual goods. We demonstrate that the demand that drives the value exhibits non Gaussian "fat tails" and typical fluctuations which grow with time interval with a Hurst exponent of 0.7.

cond-mat.stat-mech↗