2,398 research outputs found
Central European foreign exchange markets: a cross-spectral analysis of the 2007 financial crisis
This paper investigates co-movements between currency markets of Czech Republic, Poland, Hungary, Slovakia and the Euro in the year following the drying up of money markets in August 2007. The paper shows that assessing the degree of foreign currency co-movement by correlation can lead to concluding, erroneously, that financial contagion has not occurred. Using cross-spectral methods, the paper shows that defining contagion as changes in the structure of co-movements of asset prices encompasses more of the complex nature of exchange rate dynamics. What is shown is that, following August 2007, there is increased in the intensity of co-movements, but non-linearly. Focusing on the activities of a mix of banks and currency managers, it is suggested that changes in the structure of currency interaction present an unfavourable view of the contagion experienced by at least three of these currencies
Geometric and dynamic perspectives on phase-coherent and noncoherent chaos
Statistically distinguishing between phase-coherent and noncoherent chaotic
dynamics from time series is a contemporary problem in nonlinear sciences. In
this work, we propose different measures based on recurrence properties of
recorded trajectories, which characterize the underlying systems from both
geometric and dynamic viewpoints. The potentials of the individual measures for
discriminating phase-coherent and noncoherent chaotic oscillations are
discussed. A detailed numerical analysis is performed for the chaotic R\"ossler
system, which displays both types of chaos as one control parameter is varied,
and the Mackey-Glass system as an example of a time-delay system with
noncoherent chaos. Our results demonstrate that especially geometric measures
from recurrence network analysis are well suited for tracing transitions
between spiral- and screw-type chaos, a common route from phase-coherent to
noncoherent chaos also found in other nonlinear oscillators. A detailed
explanation of the observed behavior in terms of attractor geometry is given.Comment: 12 pages, 13 figure
The topology of a discussion: the #occupy case
We analyse a large sample of the Twitter activity developed around the social
movement 'Occupy Wall Street' to study the complex interactions between the
human communication activity and the semantic content of a discussion. We use a
network approach based on the analysis of the bipartite graph @Users-#Hashtags
and of its projections: the 'semantic network', whose nodes are hashtags, and
the 'users interest network', whose nodes are users In the first instance, we
find out that discussion topics (#hashtags) present a high heterogeneity, with
the distinct role of the communication hubs where most the 'opinion traffic'
passes through. In the second case, the self-organization process of users
activity leads to the emergence of two classes of communicators: the
'professionals' and the 'amateurs'. Moreover the network presents a strong
community structure, based on the differentiation of the semantic topics, and a
high level of structural robustness when a certain set of topics are censored
and/or accounts are removed. Analysing the characteristics the @Users-#Hashtags
network we can distinguish three phases of the discussion about the movement.
Each phase corresponds to specific moment of the movement: from declaration of
intent, organisation and development and the final phase of political
reactions. Each phase is characterised by the presence of specific #hashtags in
the discussion. Keywords: Twitter, Network analysisComment: 13 pages, 9 figure
High connectivity among locally adapted populations of a marine fish (Menidia menidia)
Author Posting. © Ecological Society of America, 2010. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Ecology 91 (2010): 3526â3537, doi:10.1890/09-0548.1.Patterns of connectivity are important in understanding the geographic scale of local adaptation in marine populations. While natural selection can lead to local adaptation, high connectivity can diminish the potential for such adaptation to occur. Connectivity, defined as the exchange of individuals among subpopulations, is presumed to be significant in most marine species due to life histories that include widely dispersive stages. However, evidence of local adaptation in marine species, such the Atlantic silverside, Menidia menidia, raises questions concerning the degree of connectivity. We examined geochemical signatures in the otoliths, or ear bones, of adult Atlantic silversides collected in 11 locations along the northeastern coast of the United States from New Jersey to Maine in 2004 and eight locations in 2005 using laser ablation inductively coupled plasma mass spectrometry (ICP-MS) and isotope ratio monitoring mass spectrometry (irm-MS). These signatures were then compared to baseline signatures of juvenile fish of known origin to determine natal origin of these adult fish. We then estimated migration distances and the degree of mixing from these data. In both years, fish generally had the highest probability of originating from the same location in which they were captured (0.01â0.80), but evidence of mixing throughout the sample area was present. Furthermore, adult M. menidia exhibit highly dispersive behavior with some fish migrating over 700 km. The probability of adult fish returning to natal areas differed between years, with the probability being, on average, 0.2 higher in the second year. These findings demonstrate that marine species with largely open populations are capable of local adaptation despite apparently high gene flow.This work was funded by the National Science Foundation
(grant OCE-0425830 to D. O. Conover and grant OCE-
0134998 to S. R. Thorrold) and the New York State
Department of Environmental Conservation
Twitter-based analysis of the dynamics of collective attention to political parties
Large-scale data from social media have a significant potential to describe
complex phenomena in real world and to anticipate collective behaviors such as
information spreading and social trends. One specific case of study is
represented by the collective attention to the action of political parties. Not
surprisingly, researchers and stakeholders tried to correlate parties' presence
on social media with their performances in elections. Despite the many efforts,
results are still inconclusive since this kind of data is often very noisy and
significant signals could be covered by (largely unknown) statistical
fluctuations. In this paper we consider the number of tweets (tweet volume) of
a party as a proxy of collective attention to the party, identify the dynamics
of the volume, and show that this quantity has some information on the
elections outcome. We find that the distribution of the tweet volume for each
party follows a log-normal distribution with a positive autocorrelation of the
volume over short terms, which indicates the volume has large fluctuations of
the log-normal distribution yet with a short-term tendency. Furthermore, by
measuring the ratio of two consecutive daily tweet volumes, we find that the
evolution of the daily volume of a party can be described by means of a
geometric Brownian motion (i.e., the logarithm of the volume moves randomly
with a trend). Finally, we determine the optimal period of averaging tweet
volume for reducing fluctuations and extracting short-term tendencies. We
conclude that the tweet volume is a good indicator of parties' success in the
elections when considered over an optimal time window. Our study identifies the
statistical nature of collective attention to political issues and sheds light
on how to model the dynamics of collective attention in social media.Comment: 16 pages, 7 figures, 3 tables. Published in PLoS ON
The Association of Early Dietary Supplementation with Vitamin E with the Incidence of Ulcerative Dermatitis in Mice on a C57BL/6 Background
The purpose of this study was to ascertain if prophylactic ingestion of a diet rich in vitamin E would prevent or impede the development of ulcerative dermatitis in mice on a C57BL/6 background. Mice were fed after weaning a standard mouse diet, vitamin E (99 IU/kg), or a mouse diet fortified with vitamin E (3000 IU/ kg). Cases of ulcerative dermatitis were recorded by individuals (i.e. aware of) the diet assignment. The incidence of ulcerative dermatitis in a retrospective cohort of mice on standard diet was compared with the group on the diet fortified with vitamin E. Age was associated with ulcerative dermatitis in standard diet and vitamin E fortified diet groups, r = 0.43, p-value < 0.0001 and r = 0.18, p-value < 0.02, respectively. The average age of incidence for ulcerative dermatitis in the mice fed the standard diet was 89 weeks and for the mice fed the vitamin E diet it was 41 weeks. The unadjusted odds ratio comparing the incidence of ulcerative dermatitis between the two diet groups was 4.6 with a 95% confidence interval of (2.44, 8.58), x2 p-value < 0.0001. Therefore, there was an association between the diets and ulcerative dermatitis, with the mice on the vitamin E fortified diet having almost five times the odds of having ulcerative dermatitis compared with mice on the standard diet. Incidence of ulcerative dermatitis was not influenced by sex or genotype. Our study results show that a diet fortified in vitamin E initiated at weaning does not prevent or impede the development of ulcerative dermatitis in mice on a C57BL/6 background and on the contrary accelerate development when administered to young mice.
Partisan Asymmetries in Online Political Activity
We examine partisan differences in the behavior, communication patterns and
social interactions of more than 18,000 politically-active Twitter users to
produce evidence that points to changing levels of partisan engagement with the
American online political landscape. Analysis of a network defined by the
communication activity of these users in proximity to the 2010 midterm
congressional elections reveals a highly segregated, well clustered partisan
community structure. Using cluster membership as a high-fidelity (87% accuracy)
proxy for political affiliation, we characterize a wide range of differences in
the behavior, communication and social connectivity of left- and right-leaning
Twitter users. We find that in contrast to the online political dynamics of the
2008 campaign, right-leaning Twitter users exhibit greater levels of political
activity, a more tightly interconnected social structure, and a communication
network topology that facilitates the rapid and broad dissemination of
political information.Comment: 17 pages, 10 figures, 6 table
A meta-analysis of state-of-the-art electoral prediction from Twitter data
Electoral prediction from Twitter data is an appealing research topic. It
seems relatively straightforward and the prevailing view is overly optimistic.
This is problematic because while simple approaches are assumed to be good
enough, core problems are not addressed. Thus, this paper aims to (1) provide a
balanced and critical review of the state of the art; (2) cast light on the
presume predictive power of Twitter data; and (3) depict a roadmap to push
forward the field. Hence, a scheme to characterize Twitter prediction methods
is proposed. It covers every aspect from data collection to performance
evaluation, through data processing and vote inference. Using that scheme,
prior research is analyzed and organized to explain the main approaches taken
up to date but also their weaknesses. This is the first meta-analysis of the
whole body of research regarding electoral prediction from Twitter data. It
reveals that its presumed predictive power regarding electoral prediction has
been rather exaggerated: although social media may provide a glimpse on
electoral outcomes current research does not provide strong evidence to support
it can replace traditional polls. Finally, future lines of research along with
a set of requirements they must fulfill are provided.Comment: 19 pages, 3 table
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