40 research outputs found
The network organisation of consumer complaints
Interaction between consumers and companies can create conflict. When a
consensus is unreachable there are legal authorities to resolve the case. This
letter is a study of data from the Brazilian Department of Justice from which
we build a bipartite network of categories of complaints linked to the
companies receiving those complaints. We find the complaint categories
organised in an hierarchical way where companies only get complaints of lower
degree if they already got complaints of higher degree. The fraction of
resolved complaints for a company appears to be nearly independent on the
equity of the company but is positively correlated with the total number of
complaints received. We construct feature vectors based on the edge-weight -
the weight of an edge represents the times complaints of a category have been
filed against that company - and use these vectors to study the similarity
between the categories of complaints. From this analysis, we obtain trees
mapping the hierarchical organisation of the complaints. We also apply
principal component analysis to the set of feature vectors concluding that a
reduction of the dimensionality of these from 8827 to 27 gives an optimal
hierarchical representation.Comment: 9 pages, 6 figures, 1 tabl
Flow Motifs Reveal Limitations of the Static Framework to Represent Human interactions
Networks are commonly used to define underlying interaction structures where
infections, information, or other quantities may spread. Although the standard
approach has been to aggregate all links into a static structure, some studies
suggest that the time order in which the links are established may alter the
dynamics of spreading. In this paper, we study the impact of the time ordering
in the limits of flow on various empirical temporal networks. By using a random
walk dynamics, we estimate the flow on links and convert the original
undirected network (temporal and static) into a directed flow network. We then
introduce the concept of flow motifs and quantify the divergence in the
representativity of motifs when using the temporal and static frameworks. We
find that the regularity of contacts and persistence of vertices (common in
email communication and face-to-face interactions) result on little differences
in the limits of flow for both frameworks. On the other hand, in the case of
communication within a dating site (and of a sexual network), the flow between
vertices changes significantly in the temporal framework such that the static
approximation poorly represents the structure of contacts. We have also
observed that cliques with 3 and 4 vertices con- taining only low-flow links
are more represented than the same cliques with all high-flow links. The
representativity of these low-flow cliques is higher in the temporal framework.
Our results suggest that the flow between vertices connected in cliques depend
on the topological context in which they are placed and in the time sequence in
which the links are established. The structure of the clique alone does not
completely characterize the potential of flow between the vertices
Structural Evolution of the Brazilian Airport Network
The aviation sector is profitable, but sensitive to economic fluctuations,
geopolitical constraints and governmental regulations. As for other means of
transportation, the relation between origin and destination results in a
complex map of routes, which can be complemented by information associated to
the routes themselves, for instance, frequency, traffic load or distance. The
theory of networks provides a natural framework to investigate dynamics on the
resulting structure. Here, we investigate the structure and evolution of the
Brazilian Airport Network (BAN) for several quantities: routes, connections,
passengers and cargo. Some structural features are in accordance with previous
results of other airport networks. The analysis of the evolution of the BAN
shows that its structure is dynamic, with changes in the relative relevance of
some airports and routes. The results indicate that the connections converge to
specific routes. The network shrinks at the route level but grows in number of
passengers and amount of cargo, which more than doubled during the period
studied.Comment: 10 pages, 8 figures, 2 tables. The analysis moved from an
airport-based network to a city-based network. The conclusions were
unaffecte
A network-based strategy of price correlations for optimal cryptocurrency portfolios
A cryptocurrency is a digital asset maintained by a decentralised system
using cryptography. Investors in this emerging digital market are exploring the
profitability potential of portfolios in place of single coins. Portfolios are
particularly useful given that price forecasting in such a volatile market is
challenging. The crypto market is a self-organised complex system where the
complex inter-dependencies between the cryptocurrencies may be exploited to
understand the market dynamics and build efficient portfolios. In this letter,
we use network methods to identify highly decorrelated cryptocurrencies to
create diversified portfolios using the Markowitz Portfolio Theory agnostic to
future market behaviour. The performance of our network-based portfolios is
optimal with 46 coins and superior to benchmarks up to an investment horizon of
14 days, reaching up to 1,066% average expected return within 1 day, with
reasonable associated risks. We also show that popular cryptocurrencies are
typically not included in the optimal portfolios. Past price correlations
reduce risk and may improve the performance of crypto portfolios in comparison
to methodologies based exclusively on price auto-correlations. Short-term
crypto investments may be competitive to traditional high-risk investments such
as the stock market or commodity market but call for caution given the high
variability of prices.Comment: Comments welcome
Fast but multi-partisan: Bursts of communication increase opinion diversity in the temporal Deffuant model
Human interactions create social networks forming the backbone of societies.
Individuals adjust their opinions by exchanging information through social
interactions. Two recurrent questions are whether social structures promote
opinion polarisation or consensus in societies and whether polarisation can be
avoided, particularly on social media. In this paper, we hypothesise that not
only network structure but also the timings of social interactions regulate the
emergence of opinion clusters. We devise a temporal version of the Deffuant
opinion model where pairwise interactions follow temporal patterns and show
that burstiness alone is sufficient to refrain from consensus and polarisation
by promoting the reinforcement of local opinions. Individuals self-organise
into a multi-partisan society due to network clustering, but the diversity of
opinion clusters further increases with burstiness, particularly when
individuals have low tolerance and prefer to adjust to similar peers. The
emergent opinion landscape is well-balanced regarding clusters' size, with a
small fraction of individuals converging to extreme opinions. We thus argue
that polarisation is more likely to emerge in social media than offline social
networks because of the relatively low social clustering observed online.
Counter-intuitively, strengthening online social networks by increasing social
redundancy may be a venue to reduce polarisation and promote opinion diversity.Comment: 9 pages, 6 figures. Comments (e.g. missing references, suggestions,
...) are welcome
Size dependent word frequencies and translational invariance of books
It is shown that a real novel shares many characteristic features with a null
model in which the words are randomly distributed throughout the text. Such a
common feature is a certain translational invariance of the text. Another is
that the functional form of the word-frequency distribution of a novel depends
on the length of the text in the same way as the null model. This means that an
approximate power-law tail ascribed to the data will have an exponent which
changes with the size of the text-section which is analyzed. A further
consequence is that a novel cannot be described by text-evolution models like
the Simon model. The size-transformation of a novel is found to be well
described by a specific Random Book Transformation. This size transformation in
addition enables a more precise determination of the functional form of the
word-frequency distribution. The implications of the results are discussed.Comment: 10 pages, 2 appendices (6 pages), 5 figure
The meta book and size-dependent properties of written language
Evidence is given for a systematic text-length dependence of the power-law
index gamma of a single book. The estimated gamma values are consistent with a
monotonic decrease from 2 to 1 with increasing length of a text. A direct
connection to an extended Heap's law is explored. The infinite book limit is,
as a consequence, proposed to be given by gamma = 1 instead of the value
gamma=2 expected if the Zipf's law was ubiquitously applicable. In addition we
explore the idea that the systematic text-length dependence can be described by
a meta book concept, which is an abstract representation reflecting the
word-frequency structure of a text. According to this concept the
word-frequency distribution of a text, with a certain length written by a
single author, has the same characteristics as a text of the same length pulled
out from an imaginary complete infinite corpus written by the same author.Comment: 7 pages, 6 figures, 1 tabl
Bad news travels fast! | NotÃcia ruim corre depressa!
Many proverbs are created through everyday experience. Although many of them are readily understood by ordinary people, the more detailed view generates many questions and doubts related to their credibility. Motivated by one of these proverbs, in the present paper, we analyse propagation of news in the network of electronic contacts (e-mails). More specifically, we propose transmission protocols intended to reproduce properties of real systems. These protocols are simulated in a real e-mail network and in the random network proposed by p. Erdos and a. Rényi prize. The results suggest that news spreads faster in the random network. The hubs in the real network tend to attract the news, in prejudice to the less connected nodes
Analyzing and Modeling Real-World Phenomena with Complex Networks: A Survey of Applications
The success of new scientific areas can be assessed by their potential for
contributing to new theoretical approaches and in applications to real-world
problems. Complex networks have fared extremely well in both of these aspects,
with their sound theoretical basis developed over the years and with a variety
of applications. In this survey, we analyze the applications of complex
networks to real-world problems and data, with emphasis in representation,
analysis and modeling, after an introduction to the main concepts and models. A
diversity of phenomena are surveyed, which may be classified into no less than
22 areas, providing a clear indication of the impact of the field of complex
networks.Comment: 103 pages, 3 figures and 7 tables. A working manuscript, suggestions
are welcome
Canagliflozin and renal outcomes in type 2 diabetes and nephropathy
BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to <90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], >300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of <15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P<0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P<0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years