23,551 research outputs found
Model reproduces individual, group and collective dynamics of human contact networks
Empirical data on the dynamics of human face-to-face interactions across a variety of social venues have recently revealed a number of context-independent structural and temporal properties of human contact networks. This universality suggests that some basic mechanisms may be responsible for the unfolding of human interactions in the physical space. Here we discuss a simple model that reproduces the empirical distributions for the individual, group and collective dynamics of face-to-face contact networks. The model describes agents that move randomly in a two-dimensional space and tend to stop when meeting âattractiveâ peers, and reproduces accurately the empirical distributions.Postprint (author's final draft
Recommended from our members
Model reproduces individual, group and collective dynamics of human contact networks
Empirical data on the dynamics of human face-to-face interactions across a variety of social venues have recently revealed a number of context-independent structural and temporal properties of human contact networks. This universality suggests that some basic mechanisms may be responsible for the unfolding of human interactions in the physical space. Here we discuss a simple model that reproduces the empirical distributions for the individual, group and collective dynamics of face-to-face contact networks. The model describes agents that move randomly in a two-dimensional space and tend to stop when meeting "attractive" peers, and reproduces accurately the empirical distributions
The roundtable: an abstract model of conversation dynamics
Is it possible to abstract a formal mechanism originating schisms and
governing the size evolution of social conversations? In this work a
constructive solution to such problem is proposed: an abstract model of a
generic N-party turn-taking conversation. The model develops from simple yet
realistic assumptions derived from experimental evidence, abstracts from
conversation content and semantics while including topological information, and
is driven by stochastic dynamics. We find that a single mechanism - namely the
dynamics of conversational party's individual fitness, as related to
conversation size - controls the development of the self-organized schisming
phenomenon. Potential generalizations of the model - including individual
traits and preferences, memory effects and more elaborated conversational
topologies - may find important applications also in other fields of research,
where dynamically-interacting and networked agents play a fundamental role.Comment: 18 pages, 4 figures, to be published in Journal of Artificial
Societies and Social Simulatio
Mechanical cell-matrix feedback explains pairwise and collective endothelial cell behavior in vitro
In vitro cultures of endothelial cells are a widely used model system of the
collective behavior of endothelial cells during vasculogenesis and
angiogenesis. When seeded in an extracellular matrix, endothelial cells can
form blood vessel-like structures, including vascular networks and sprouts.
Endothelial morphogenesis depends on a large number of chemical and mechanical
factors, including the compliancy of the extracellular matrix, the available
growth factors, the adhesion of cells to the extracellular matrix, cell-cell
signaling, etc. Although various computational models have been proposed to
explain the role of each of these biochemical and biomechanical effects, the
understanding of the mechanisms underlying in vitro angiogenesis is still
incomplete. Most explanations focus on predicting the whole vascular network or
sprout from the underlying cell behavior, and do not check if the same model
also correctly captures the intermediate scale: the pairwise cell-cell
interactions or single cell responses to ECM mechanics. Here we show, using a
hybrid cellular Potts and finite element computational model, that a single set
of biologically plausible rules describing (a) the contractile forces that
endothelial cells exert on the ECM, (b) the resulting strains in the
extracellular matrix, and (c) the cellular response to the strains, suffices
for reproducing the behavior of individual endothelial cells and the
interactions of endothelial cell pairs in compliant matrices. With the same set
of rules, the model also reproduces network formation from scattered cells, and
sprouting from endothelial spheroids. Combining the present mechanical model
with aspects of previously proposed mechanical and chemical models may lead to
a more complete understanding of in vitro angiogenesis.Comment: 25 pages, 6 figures, accepted for publication in PLoS Computational
Biolog
Robust modeling of human contact networks across different scales and proximity-sensing techniques
The problem of mapping human close-range proximity networks has been tackled
using a variety of technical approaches. Wearable electronic devices, in
particular, have proven to be particularly successful in a variety of settings
relevant for research in social science, complex networks and infectious
diseases dynamics. Each device and technology used for proximity sensing (e.g.,
RFIDs, Bluetooth, low-power radio or infrared communication, etc.) comes with
specific biases on the close-range relations it records. Hence it is important
to assess which statistical features of the empirical proximity networks are
robust across different measurement techniques, and which modeling frameworks
generalize well across empirical data. Here we compare time-resolved proximity
networks recorded in different experimental settings and show that some
important statistical features are robust across all settings considered. The
observed universality calls for a simplified modeling approach. We show that
one such simple model is indeed able to reproduce the main statistical
distributions characterizing the empirical temporal networks
The Roundtable: An Abstract Model of Conversation Dynamics
Is it possible to abstract a formal mechanism originating schisms and governing the size evolution of social conversations? In this work we propose a constructive solution to this problem: an abstract model of a generic N-party turn-taking conversation. The model develops from simple yet realistic assumptions derived from experimental evidence, abstracts from conversation content and semantics while including topological information, and is driven by stochastic dynamics. We find that a single mechanism, namely the dynamics of conversational party\'s individual fitness as related to conversation size, controls the development of the self-organized schisming phenomenon. Potential generalizations of the model - including individual traits and preferences, memory effects and more elaborated conversational topologies - may find important applications also in other fields of research, where dynamically-interacting and networked agents play a fundamental role.ABM, Complexity, Turn-Taking Dynamics, Schism, Stochastic Dynamics
Validation of Dunbar's number in Twitter conversations
Modern society's increasing dependency on online tools for both work and
recreation opens up unique opportunities for the study of social interactions.
A large survey of online exchanges or conversations on Twitter, collected
across six months involving 1.7 million individuals is presented here. We test
the theoretical cognitive limit on the number of stable social relationships
known as Dunbar's number. We find that users can entertain a maximum of 100-200
stable relationships in support for Dunbar's prediction. The "economy of
attention" is limited in the online world by cognitive and biological
constraints as predicted by Dunbar's theory. Inspired by this empirical
evidence we propose a simple dynamical mechanism, based on finite priority
queuing and time resources, that reproduces the observed social behavior.Comment: 8 pages, 6 figure
- âŠ