908 research outputs found
Weblog patterns and human dynamics with decreasing interest
Weblog is the fourth way of network exchange after Email, BBS and MSN. Most
bloggers begin to write blogs with great interest, and then their interests
gradually achieve a balance with the passage of time. In order to describe the
phenomenon that people's interest in something gradually decreases until it
reaches a balance, we first propose the model that describes the attenuation of
interest and reflects the fact that people's interest becomes more stable after
a long time. We give a rigorous analysis on this model by non-homogeneous
Poisson processes. Our analysis indicates that the interval distribution of
arrival-time is a mixed distribution with exponential and power-law feature,
that is, it is a power law with an exponential cutoff. Second, we collect blogs
in ScienceNet.cn and carry on empirical studies on the interarrival time
distribution. The empirical results agree well with the analytical result,
obeying a special power law with the exponential cutoff, that is, a special
kind of Gamma distribution. These empirical results verify the model, providing
an evidence for a new class of phenomena in human dynamics. In human dynamics
there are other distributions, besides power-law distributions. These findings
demonstrate the variety of human behavior dynamics.Comment: 8 pages, 1 figure
Circadian pattern and burstiness in mobile phone communication
The temporal communication patterns of human individuals are known to be
inhomogeneous or bursty, which is reflected as the heavy tail behavior in the
inter-event time distribution. As the cause of such bursty behavior two main
mechanisms have been suggested: a) Inhomogeneities due to the circadian and
weekly activity patterns and b) inhomogeneities rooted in human task execution
behavior. Here we investigate the roles of these mechanisms by developing and
then applying systematic de-seasoning methods to remove the circadian and
weekly patterns from the time-series of mobile phone communication events of
individuals. We find that the heavy tails in the inter-event time distributions
remain robustly with respect to this procedure, which clearly indicates that
the human task execution based mechanism is a possible cause for the remaining
burstiness in temporal mobile phone communication patterns.Comment: 17 pages, 12 figure
Timing interactions in social simulations: The voter model
The recent availability of huge high resolution datasets on human activities
has revealed the heavy-tailed nature of the interevent time distributions. In
social simulations of interacting agents the standard approach has been to use
Poisson processes to update the state of the agents, which gives rise to very
homogeneous activity patterns with a well defined characteristic interevent
time. As a paradigmatic opinion model we investigate the voter model and review
the standard update rules and propose two new update rules which are able to
account for heterogeneous activity patterns. For the new update rules each node
gets updated with a probability that depends on the time since the last event
of the node, where an event can be an update attempt (exogenous update) or a
change of state (endogenous update). We find that both update rules can give
rise to power law interevent time distributions, although the endogenous one
more robustly. Apart from that for the exogenous update rule and the standard
update rules the voter model does not reach consensus in the infinite size
limit, while for the endogenous update there exist a coarsening process that
drives the system toward consensus configurations.Comment: Book Chapter, 23 pages, 9 figures, 5 table
Early risk factors for adolescent antisocial behaviour: an Australian longitudinal study
Objective: This investigation utilizes data from an Australian longitudinal study to identify early risk factors for adolescent antisocial behaviour. Method: Analyses are based on data from the Mater University Study of Pregnancy, an on-going longitudinal investigation of women’s and children’s health and development involving over 8000 participants. Five types of risk factors (child characteristics, perinatal factors, maternal/familial characteristics, maternal pre- and post-natal substance use and parenting practices) were included in analyses and were based on maternal reports, child assessments and medical records. Adolescent antisocial behaviour was measured when children were 14 years old, using the delinquency subscale of the Child Behaviour Checklist. Results: Based on a series of logistic regression models, significant risk factors for adolescent antisocial behaviour included children’s prior problem behaviour (i.e. aggression and attention/restlessness problems at age 5 years) and marital instability, which doubled or tripled the odds of antisocial behaviour. Perinatal factors, maternal substance use, and parenting practices were relatively poor predictors of antisocial behaviour. Conclusions: Few studies have assessed early predictors of antisocial behaviour in Australia and the current results can be used to inform prevention programs that target risk factors likely to lead to problem outcomes for Australian youth
Local variation of hashtag spike trains and popularity in Twitter
We draw a parallel between hashtag time series and neuron spike trains. In
each case, the process presents complex dynamic patterns including temporal
correlations, burstiness, and all other types of nonstationarity. We propose
the adoption of the so-called local variation in order to uncover salient
dynamics, while properly detrending for the time-dependent features of a
signal. The methodology is tested on both real and randomized hashtag spike
trains, and identifies that popular hashtags present regular and so less bursty
behavior, suggesting its potential use for predicting online popularity in
social media.Comment: 7 pages, 7 figure
Statistical mixing and aggregation in Feller diffusion
We consider Feller mean-reverting square-root diffusion, which has been
applied to model a wide variety of processes with linearly state-dependent
diffusion, such as stochastic volatility and interest rates in finance, and
neuronal and populations dynamics in natural sciences. We focus on the
statistical mixing (or superstatistical) process in which the parameter related
to the mean value can fluctuate - a plausible mechanism for the emergence of
heavy-tailed distributions. We obtain analytical results for the associated
probability density function (both stationary and time dependent), its
correlation structure and aggregation properties. Our results are applied to
explain the statistics of stock traded volume at different aggregation scales.Comment: 16 pages, 3 figures. To be published in Journal of Statistical
Mechanics: Theory and Experimen
Universal features of correlated bursty behaviour
Inhomogeneous temporal processes, like those appearing in human
communications, neuron spike trains, and seismic signals, consist of
high-activity bursty intervals alternating with long low-activity periods. In
recent studies such bursty behavior has been characterized by a fat-tailed
inter-event time distribution, while temporal correlations were measured by the
autocorrelation function. However, these characteristic functions are not
capable to fully characterize temporally correlated heterogenous behavior. Here
we show that the distribution of the number of events in a bursty period serves
as a good indicator of the dependencies, leading to the universal observation
of power-law distribution in a broad class of phenomena. We find that the
correlations in these quite different systems can be commonly interpreted by
memory effects and described by a simple phenomenological model, which displays
temporal behavior qualitatively similar to that in real systems
Random Walks on Stochastic Temporal Networks
In the study of dynamical processes on networks, there has been intense focus
on network structure -- i.e., the arrangement of edges and their associated
weights -- but the effects of the temporal patterns of edges remains poorly
understood. In this chapter, we develop a mathematical framework for random
walks on temporal networks using an approach that provides a compromise between
abstract but unrealistic models and data-driven but non-mathematical
approaches. To do this, we introduce a stochastic model for temporal networks
in which we summarize the temporal and structural organization of a system
using a matrix of waiting-time distributions. We show that random walks on
stochastic temporal networks can be described exactly by an
integro-differential master equation and derive an analytical expression for
its asymptotic steady state. We also discuss how our work might be useful to
help build centrality measures for temporal networks.Comment: Chapter in Temporal Networks (Petter Holme and Jari Saramaki
editors). Springer. Berlin, Heidelberg 2013. The book chapter contains minor
corrections and modifications. This chapter is based on arXiv:1112.3324,
which contains additional calculations and numerical simulation
A Human Development Framework for CO2 Reductions
Although developing countries are called to participate in CO2 emission
reduction efforts to avoid dangerous climate change, the implications of
proposed reduction schemes in human development standards of developing
countries remain a matter of debate. We show the existence of a positive and
time-dependent correlation between the Human Development Index (HDI) and per
capita CO2 emissions from fossil fuel combustion. Employing this empirical
relation, extrapolating the HDI, and using three population scenarios, the
cumulative CO2 emissions necessary for developing countries to achieve
particular HDI thresholds are assessed following a Development As Usual
approach (DAU). If current demographic and development trends are maintained,
we estimate that by 2050 around 85% of the world's population will live in
countries with high HDI (above 0.8). In particular, 300Gt of cumulative CO2
emissions between 2000 and 2050 are estimated to be necessary for the
development of 104 developing countries in the year 2000. This value represents
between 20% to 30% of previously calculated CO2 budgets limiting global warming
to 2{\deg}C. These constraints and results are incorporated into a CO2
reduction framework involving four domains of climate action for individual
countries. The framework reserves a fair emission path for developing countries
to proceed with their development by indexing country-dependent reduction rates
proportional to the HDI in order to preserve the 2{\deg}C target after a
particular development threshold is reached. Under this approach, global
cumulative emissions by 2050 are estimated to range from 850 up to 1100Gt of
CO2. These values are within the uncertainty range of emissions to limit global
temperatures to 2{\deg}C.Comment: 14 pages, 7 figures, 1 tabl
The Atlantic Ocean at the last glacial maximum: 1. Objective mapping of the GLAMAP sea-surface conditions
Recent efforts of the German paleoceanographic community have resulted in a unique data set of reconstructed sea-surface temperature for the Atlantic Ocean during the Last Glacial Maximum, plus estimates for the extents of glacial sea ice. Unlike prior attempts, the contributing research groups based their data on a common definition of the Last Glacial Maximum chronozone and used the same modern reference data for calibrating the different transfer techniques. Furthermore, the number of processed sediment cores was vastly increased. Thus the new data is a significant advance not only with respect to quality, but also to quantity. We integrate these new data and provide monthly data sets of global sea-surface temperature and ice cover, objectively interpolated onto a regular 1°x1° grid, suitable for forcing or validating numerical ocean and atmosphere models. This set is compared to an existing subjective interpolation of the same base data, in part by employing an ocean circulation model. For the latter purpose, we reconstruct sea surface salinity from the new temperature data and the available oxygen isotope measurements
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