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

Citizen Social Lab: a digital platform for human behavior 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 limitations in terms of subject pool or decisions' context, 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 data collection protocols to maintain the same data quality that one can obtain in the laboratories. In this article 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 rigor, 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, the satisfaction level of participants, or the technical parameters that demonstrate the robustness of the platform and the quality of the data collected

Els nous reptes del periodisme : fake news i big data

Obra col·lectiva biennal, creada per l'Institut de la Comunicació de la Universitat Autònoma de Barcelona (InCom-UAB), l'any 2000. La desena edició, corresponent al bienni 2017-2018, va comptar amb el suport de la Generalitat de Catalunya; el patrocini de Naturgy; la col·laboració de l'Ajuntament de Barcelona; la subscripció institucional de la Societat Catalana de Comunicació (filial de l'Institut d'Estudis Catalans); i la col·laboració científica de Comscore, Estudio General de Medios (EGM)/Asociación para la Investigación de Medios de Comunicación (AIMC), l'Observatori de la Comunicació a Catalunya, i el Portal de la Comunicació (InCom-UAB).En el marc del Grup Internacional d'Estudis sobre Comunicació i Cultura (InCom-UAB), reconegut com a Grup Consolidat de Recerca de la Generalitat de Catalunya per al període 2017-2020 (Referència de concessió 2017 SGR 00760).Les darreres campanyes d'Obama i Trump als Estats Units han estat un exemple de com la política ha fet de les xarxes socials el seu espai de combat. L'anàlisi i l'explotació de dades massives (big data) s'han convertit en una eina fonamental per tal de prendre decisions determinants per influir en l'opinió pública i, finalment, en els resultats electorals. Un altre element central d'aquest combat és el relat periodístic, font de la majoria de continguts que es difonen en les xarxes socials. En aquest escenari, les notícies falses o enganyoses (fake news) han esdevingut un dels principals instruments polítics, i han evidenciat la crisi de legitimitat per la qual passa el periodisme actual. El cas català i totes les informacions sorgides al voltant del referèndum de l'1 d'octubre de 2017 en són un clar exponent

Quantitative account of social interactions in a mental health care ecosystem: cooperation, trust and collective action

Mental disorders have an enormous impact in our society, both in personal terms and in the economic costs associated with their treatment. In order to scale up services and bring down costs, administrations are starting to promote social interactions as key to care provision. We analyze quantitatively the importance of communities for effective mental health care, considering all community members involved. By means of citizen science practices, we have designed a suite of games that allow to probe into different behavioral traits of the role groups of the ecosystem. The evidence reinforces the idea of community social capital, with caregivers and professionals playing a leading role. Yet, the cost of collective action is mainly supported by individuals with a mental condition - which unveils their vulnerability. The results are in general agreement with previous findings but, since we broaden the perspective of previous studies, we are also able to find marked differences in the social behavior of certain groups of mental disorders. We finally point to the conditions under which cooperation among members of the ecosystem is better sustained, suggesting how virtuous cycles of inclusion and participation can be promoted in a 'care in the community' framework

Sistemes socioeconòmics i financers

Els mercats financers, entre molts altres contextos socials i econòmics, amaguen diverses relacions amb la İ sica estadísƟ ca. Sense anar més lluny, el model matemàƟ c de les coƟ tzacions fi nanceres és el mateix uƟ litzat per a la teoria de gasos o per les parơ cules en suspensió en un líquid. En aquest arƟ cle recorrem la trajectòria de l'anomenada econoİ sica des de 1900 i presentem algunes de les contribucions a la matèria feta per membres de Complexitat.CA

Resource heterogeneity leads to unjust effort distribution in climate change mitigation

Climate change mitigation is a shared global challenge that involves collective action of a set of individuals with different tendencies to cooperation. However, we lack an understanding of the effect of resource inequality when diverse actors interact together towards a common goal. Here, we report the results of a collective-risk dilemma experiment in which groups of individuals were initially given either equal or unequal endowments. We found that the effort distribution was highly inequitable, with participants with fewer resources contributing significantly more to the public goods than the richer −sometimes twice as much. An unsupervised learning algorithm classified the subjects according to their individual behavior, finding the poorest participants within two 'generous clusters' and the richest into a 'greedy cluster'. Our results suggest that policies would benefit from educating about fairness and reinforcing climate justice actions addressed to vulnerable people instead of focusing on understanding generic or global climate consequences

Coping Strategies and Social Support in a Mobile Phone Chat App Designed to Support Smoking Cessation : Qualitative Analysis

Smoking is one of the most significant factors contributing to low life expectancy, health inequalities, and illness at the worldwide scale. Smoking cessation attempts benefit from social support. Mobile phones have changed the way we communicate through the use of freely available message-oriented apps. Mobile app-based interventions for smoking cessation programs can provide interactive, supportive, and individually tailored interventions. This study aimed to identify emotions, coping strategies, beliefs, values, and cognitive evaluations of smokers who are in the process of quitting, and to analyze online social support provided through the analysis of messages posted to a chat function integrated into a mobile app. In this descriptive qualitative study, informants were smokers who participated in the chat of Tobbstop. The technique to generate information was documentary through messages collected from September 2014 through June 2016, specifically designed to support a smoking cessation intervention. A thematic content analysis of the messages applied 2 conceptual models: the Lazarus and Folkman model to assess participant's experiences and perceptions and the Cutrona model to evaluate online social support. During the study period, 11,788 text messages were posted to the chat by 101 users. The most frequent messages offered information and emotional support, and all the basic emotions were reported in the chat. The 3 most frequent coping strategies identified were physical activity, different types of treatment such as nicotine replacement, and humor. Beliefs about quitting smoking included the inevitability of weight gain and the notion that not using any type of medications is better for smoking cessation. Health and family were the values more frequently described, followed by freedom. A smoke-free environment was perceived as important to successful smoking cessation. The social support group that was developed with the app offered mainly emotional and informational support. Our analysis suggests that a chat integrated into a mobile app focused on supporting smoking cessation provides a useful tool for smokers who are in the process of quitting, by offering social support and a space to share concerns, information, or strategies

Structure and Traffic on Complex Networks

In a time when large amounts of data about social, economical, technological, and biological systems are produced in a daily bases, complex networks have become a powerful tool to represent the structure of complex systems. The advances in complex networks research have been geared towards the study of two main questions: what can we understand from a complex system by looking at its structure, and more importantly, what is the interplay between the topological and dynamical properties of complex systems. The aim of this dissertation is to review and introduce new tools and methods to measure topological and dynamical properties of complex networks. In particular, it covers two specific problems related with the two previously presented questions: the study of the community structure of complex networks, and the analysis of the dynamical properties of a communication process. The first part of the thesis is focused on the study of the community structure of complex networks, that is, how and why the nodes of the network tend to form groups in which they are highly interconnected. The understanding of this problem is key to characterize the internal organization of complex systems, obtaining better insights about the dynamical behavior of their components. In this part we present an exhaustive review of the community structure identification problem, explaining the limitations of the current existing methods, and we introduce a new method to extract the community structure based on the extremal optimization algorithm. We also present several improvements that increase the efficiency and accuracy of current community identification methods and an exhaustive benchmark of the results obtained when applying this new method to the standard network metrics. These results show that the extremal optimization method and its modifications are one of the fastest and most accurate options to identify the community structure of a network. The second part of the thesis is devoted to the study of some dynamical properties of communication processes over complex networks. Using a simple traffic model we analyze the changes observed on some properties when we introduce congestion in the network: the scaling of the fluctuations and the dynamical robustness. First, we present the scaling of the fluctuations in order to provide a large-scale dynamical characterization of the traffic flow. The idea is that there are a large number of real complex systems that show a scaling relation between the average flux and the variability of this flux. The understanding of the scaling relation presented in the dissertation will help us design better traffic models. And second, we study the dynamical robustness of the traffic, defined as the capability of maintaining the efficiency of the communication when we remove a fraction of nodes of the network. We show that there is a dynamical percolation threshold that splits the network due to the congestion before the topological percolation threshold

Differences in Collaboration Patterns across Discipline, Career Stage, and Gender

DOI: 10.1371/journal.pbio.1002573 URL: http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002573 Filiació URV: SI Inclòs a la memòria: SICollaboration plays an increasingly important role in promoting research productivity and impact. What remains unclear is whether female and male researchers in science, technology, engineering, and mathematical (STEM) disciplines differ in their collaboration propensity. Here, we report on an empirical analysis of the complete publication records of 3,980 faculty members in six STEM disciplines at select U.S. research universities. We find that female faculty have significantly fewer distinct co-authors over their careers than males, but that this difference can be fully accounted for by females’ lower publication rate and shorter career lengths. Next, we find that female scientists have a lower probability of repeating previous co-authors than males, an intriguing result because prior research shows that teams involving new collaborations produce work with higher impact. Finally, we find evidence for gender segregation in some sub-disciplines in molecular biology, in particular in genomics where we find female faculty to be clearly under-represented

Sonido, interacción y redes, febrero 2012

Material docent de la Universitat Oberta de Catalunya.Material docente de la "Universitat Oberta de Catalunya".Learning material of the "Universitat Oberta de Catalunya"