161 research outputs found
On Universality in Human Correspondence Activity
Identifying and modeling patterns of human activity has important
ramifications in applications ranging from predicting disease spread to
optimizing resource allocation. Because of its relevance and availability,
written correspondence provides a powerful proxy for studying human activity.
One school of thought is that human correspondence is driven by responses to
received correspondence, a view that requires distinct response mechanism to
explain e-mail and letter correspondence observations. Here, we demonstrate
that, like e-mail correspondence, the letter correspondence patterns of 16
writers, performers, politicians, and scientists are well-described by the
circadian cycle, task repetition and changing communication needs. We confirm
the universality of these mechanisms by properly rescaling letter and e-mail
correspondence statistics to reveal their underlying similarity.Comment: 17 pages, 3 figures, 1 tabl
A Poissonian explanation for heavy-tails in e-mail communication
Patterns of deliberate human activity and behavior are of utmost importance
in areas as diverse as disease spread, resource allocation, and emergency
response. Because of its widespread availability and use, e-mail correspondence
provides an attractive proxy for studying human activity. Recently, it was
reported that the probability density for the inter-event time between
consecutively sent e-mails decays asymptotically as , with
. The slower than exponential decay of the inter-event time
distribution suggests that deliberate human activity is inherently
non-Poissonian. Here, we demonstrate that the approximate power-law scaling of
the inter-event time distribution is a consequence of circadian and weekly
cycles of human activity. We propose a cascading non-homogeneous Poisson
process which explicitly integrates these periodic patterns in activity with an
individual's tendency to continue participating in an activity. Using standard
statistical techniques, we show that our model is consistent with the empirical
data. Our findings may also provide insight into the origins of heavy-tailed
distributions in other complex systems.Comment: 9 pages, 5 figure
Sandpile model on an optimized scale-free network on Euclidean space
Deterministic sandpile models are studied on a cost optimized
Barab\'asi-Albert (BA) scale-free network whose nodes are the sites of a square
lattice. For the optimized BA network, the sandpile model has the same critical
behaviour as the BTW sandpile, whereas for the un-optimized BA network the
critical behaviour is mean-field like.Comment: Five pages, four figure
The topological relationship between the large-scale attributes and local interaction patterns of complex networks
Recent evidence indicates that the abundance of recurring elementary
interaction patterns in complex networks, often called subgraphs or motifs,
carry significant information about their function and overall organization.
Yet, the underlying reasons for the variable quantity of different subgraph
types, their propensity to form clusters, and their relationship with the
networks' global organization remain poorly understood. Here we show that a
network's large-scale topological organization and its local subgraph structure
mutually define and predict each other, as confirmed by direct measurements in
five well studied cellular networks. We also demonstrate the inherent existence
of two distinct classes of subgraphs, and show that, in contrast to the
low-density type II subgraphs, the highly abundant type I subgraphs cannot
exist in isolation but must naturally aggregate into subgraph clusters. The
identified topological framework may have important implications for our
understanding of the origin and function of subgraphs in all complex networks.Comment: pape
Inheritance patterns in citation networks reveal scientific memes
Memes are the cultural equivalent of genes that spread across human culture
by means of imitation. What makes a meme and what distinguishes it from other
forms of information, however, is still poorly understood. Our analysis of
memes in the scientific literature reveals that they are governed by a
surprisingly simple relationship between frequency of occurrence and the degree
to which they propagate along the citation graph. We propose a simple
formalization of this pattern and we validate it with data from close to 50
million publication records from the Web of Science, PubMed Central, and the
American Physical Society. Evaluations relying on human annotators, citation
network randomizations, and comparisons with several alternative approaches
confirm that our formula is accurate and effective, without a dependence on
linguistic or ontological knowledge and without the application of arbitrary
thresholds or filters.Comment: 8 two-column pages, 5 figures; accepted for publication in Physical
Review
Systemic importance of financial institutions: regulations, research, open issues, proposals
In the field of risk management, scholars began to bring together the quantitative methodologies with the banking management issues about 30 years ago, with a special focus on market, credit and operational risks. After the systemic effects of banks defaults during the recent financial crisis,
and despite a huge amount of literature in the last years concerning the systemic risk, no standard methodologies have been set up to now. Even the new Basel 3 regulation has adopted a heuristic indicator-based approach, quite far from an effective quantitative tool. In this paper, we refer to the different pieces of the puzzle: definition of systemic risk, a set of coherent and useful measures, the computability of these measures, the data set structure. In this challenging field, we aim to build a comprehensive picture of the state of the art, to illustrate the open issues, and to outline some paths for a more successful future research. This work appropriately integrates other useful surveys and it is directed to both academic researchers and practitioners
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