231 research outputs found
Citizen Social Lab: A digital platform for human behaviour experimentation within a citizen science framework
Cooperation is one of the behavioral traits that define human beings, however
we are still trying to understand why humans cooperate. Behavioral experiments
have been largely conducted to shed light into the mechanisms behind
cooperation and other behavioral traits. However, most of these experiments
have been conducted in laboratories with highly controlled experimental
protocols but with varied limitations which limits the reproducibility and the
generalization of the results obtained. In an attempt to overcome these
limitations, some experimental approaches have moved human behavior
experimentation from laboratories to public spaces, where behaviors occur
naturally, and have opened the participation to the general public within the
citizen science framework. Given the open nature of these environments, it is
critical to establish the appropriate protocols to maintain the same data
quality that one can obtain in the laboratories. Here, we introduce Citizen
Social Lab, a software platform designed to be used in the wild using citizen
science practices. The platform allows researchers to collect data in a more
realistic context while maintaining the scientific rigour, and it is structured
in a modular and scalable way so it can also be easily adapted for online or
brick-and-mortar experimental laboratories. Following citizen science
guidelines, the platform is designed to motivate a more general population into
participation, but also to promote engaging and learning of the scientific
research process. We also review the main results of the experiments performed
using the platform up to now, and the set of games that each experiment
includes. Finally, we evaluate some properties of the platform, such as the
heterogeneity of the samples of the experiments and their satisfaction level,
and the parameters that demonstrate the robustness of the platform and the
quality of the data collected.Comment: 17 pages, 11 figures and 4 table
Quantum Navigation and Ranking in Complex Networks
Complex networks are formal frameworks capturing the interdependencies
between the elements of large systems and databases. This formalism allows to
use network navigation methods to rank the importance that each constituent has
on the global organization of the system. A key example is Pagerank navigation
which is at the core of the most used search engine of the World Wide Web.
Inspired in this classical algorithm, we define a quantum navigation method
providing a unique ranking of the elements of a network. We analyze the
convergence of quantum navigation to the stationary rank of networks and show
that quantumness decreases the number of navigation steps before convergence.
In addition, we show that quantum navigation allows to solve degeneracies found
in classical ranks. By implementing the quantum algorithm in real networks, we
confirm these improvements and show that quantum coherence unveils new
hierarchical features about the global organization of complex systems.Comment: title changed, more real networks analyzed, version published in
scientific report
Digital Learners in Scientific Literature: Design and Implementation of a Systematic Review from 2001 to 2010
En la última década han surgido numerosas denominaciones que tratan de definir a una nueva generación de estudiantes. Una generación digital que ha crecido rodeada de tecnología y que, supuestamente, poseen unas características comunes y diferenciadas de las anteriores. El objetivo de este artículo es analizar la evolución y la relación de estas denominaciones en la literatura científica. Para ello, se muestra el proceso de construcción de una herramienta y el diseño de una estrategia para la revisión sistemática de esta temática en los artículos publicados en ISI Web of Science entre 2001 y 2010, así como los principales resultados.In the last decade have emerged numerous denominations that seek to define a new generation of students. A digital generation that has grown up surrounded by technology and supposedly therefore has common and distinct characteristics. The aim of this paper is to investigate the evolution and the relationship of these denominations in the scientific literature. For this purpose, a tool and a strategy is built and designed for the systematic review of this subject in articles published in ISI Web of Science from 2001 to 2010, and the main results are shown.Ministerio de Educación (España) PR20100394Ministerio de Ciencia e Innovación (España) EDU2008-0147
On the universality of the scaling of fluctuations in traffic on complex networks
We study the scaling of fluctuations with the mean of traffic in complex
networks using a model where the arrival and departure of "packets" follow
exponential distributions, and the processing capability of nodes is either
unlimited or finite. The model presents a wide variety of exponents between 1/2
and 1 for this scaling, revealing their dependence on the few parameters
considered, and questioning the existence of universality classes. We also
report the experimental scaling of the fluctuations in the Internet for the
Abilene backbone network. We found scaling exponents between 0.71 and 0.86 that
do not fit with the exponent 1/2 reported in the literature.Comment: 4 pages, 4 figure
Community detection in complex networks using Extremal Optimization
We propose a novel method to find the community structure in complex networks
based on an extremal optimization of the value of modularity. The method
outperforms the optimal modularity found by the existing algorithms in the
literature. We present the results of the algorithm for computer simulated and
real networks and compare them with other approaches. The efficiency and
accuracy of the method make it feasible to be used for the accurate
identification of community structure in large complex networks.Comment: 4 pages, 4 figure
Tracking Traders' Understanding of the Market Using e-Communication Data
Tracking the volume of keywords in Internet searches, message boards, or
Tweets has provided an alternative for following or predicting associations
between popular interest or disease incidences. Here, we extend that research
by examining the role of e-communications among day traders and their
collective understanding of the market. Our study introduces a general method
that focuses on bundles of words that behave differently from daily
communication routines, and uses original data covering the content of instant
messages among all day traders at a trading firm over a 40-month period.
Analyses show that two word bundles convey traders' understanding of same day
market events and potential next day market events. We find that when market
volatility is high, traders' communications are dominated by same day events,
and when volatility is low, communications are dominated by next day events. We
show that the stronger the traders' attention to either same day or next day
events, the higher their collective trading performance. We conclude that
e-communication among traders is a product of mass collaboration over diverse
viewpoints that embodies unique information about their weak or strong
understanding of the market
- …