183 research outputs found
Probing Limits of Information Spread with Sequential Seeding
We consider here information spread which propagates with certain probability
from nodes just activated to their not yet activated neighbors. Diffusion
cascades can be triggered by activation of even a small set of nodes. Such
activation is commonly performed in a single stage. A novel approach based on
sequential seeding is analyzed here resulting in three fundamental
contributions. First, we propose a coordinated execution of randomized choices
to enable precise comparison of different algorithms in general. We apply it
here when the newly activated nodes at each stage of spreading attempt to
activate their neighbors. Then, we present a formal proof that sequential
seeding delivers at least as large coverage as the single stage seeding does.
Moreover, we also show that, under modest assumptions, sequential seeding
achieves coverage provably better than the single stage based approach using
the same number of seeds and node ranking. Finally, we present experimental
results showing how single stage and sequential approaches on directed and
undirected graphs compare to the well-known greedy approach to provide the
objective measure of the sequential seeding benefits. Surprisingly, applying
sequential seeding to a simple degree-based selection leads to higher coverage
than achieved by the computationally expensive greedy approach currently
considered to be the best heuristic
Interacting Spreading Processes in Multilayer Networks: A Systematic Review
© 2013 IEEE. The world of network science is fascinating and filled with complex phenomena that we aspire to understand. One of them is the dynamics of spreading processes over complex networked structures. Building the knowledge-base in the field where we can face more than one spreading process propagating over a network that has more than one layer is a challenging task, as the complexity comes both from the environment in which the spread happens and from characteristics and interplay of spreads' propagation. As this cross-disciplinary field bringing together computer science, network science, biology and physics has rapidly grown over the last decade, there is a need to comprehensively review the current state-of-the-art and offer to the research community a roadmap that helps to organise the future research in this area. Thus, this survey is a first attempt to present the current landscape of the multi-processes spread over multilayer networks and to suggest the potential ways forward
A picture is worth a thousand words: an empirical study on the influence of content visibility on diffusion processes within a virtual world
Studying information diffusion and the spread of goods in the real world and in many digital services can be extremely difficult since information about the information flows is challenging to accurately track. How information spreads has commonly been analysed from the perspective of homophily, social influence, and initial seed selection. However, in virtual worlds and virtual economies, the movements of information and goods can be precisely tracked. Therefore, these environments create laboratories for the accurate study of information diffusion characteristics that have been difficult to study in prior research. In this paper, we study how content visibility as well as sender and receiver characteristics, the relationship between them, and the types of multilayer social network layers affect content absorption and diffusion in virtual world. The results show that prior visibility of distributed content is the strongest predictor of content adoption and its further spread across networks. Among other analysed factors, the mechanics of diffusion, content quality, and content adoption by users’ neighbours on the social activity layer had very strong influences on the adoption of new content.</p
Towards effective visual analytics on multiplex and multilayer networks
In this article we discuss visualisation strategies for multiplex networks.
Since Moreno's early works on network analysis, visualisation has been one of
the main ways to understand networks thanks to its ability to summarise a
complex structure into a single representation highlighting multiple properties
of the data. However, despite the large renewed interest in the analysis of
multiplex networks, no study has proposed specialised visualisation approaches
for this context and traditional methods are typically applied instead. In this
paper we initiate a critical and structured discussion of this topic, and claim
that the development of specific visualisation methods for multiplex networks
will be one of the main drivers pushing current research results into daily
practice
Supercooled confined water and the Mode Coupling crossover temperature
We present a Molecular Dynamics study of the single particle dynamics of
supercooled water confined in a silica pore. Two dynamical regimes are found:
close to the hydrophilic substrate molecules are below the Mode Coupling
crossover temperature, , already at ambient temperature. The water closer
to the center of the pore (free water) approaches upon supercooling as
predicted by Mode Coupling Theories. For free water the crossover temperature
and crossover exponent are extracted from power-law fits to both the
diffusion coefficient and the relaxation time of the late region.Comment: To be published, Phys. Rev. Lett., 4 pages, 3 figures, revTeX, minor
changes in the figures, references added, changes in the tex
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