Speaker
Gorka Zamora-Lopez

Description A striking question in neuroscience is how the brain is capable to segregate information (process information at different places) and to simultaneously integrate information to produce a coherent, multi-sensorial, perception of reality. All neural and brain networks investigated so far share common modular and hierarchical features that are believed to aid the brain this puzzle. Motivated by this problem we investigate the capacity of different classes of hierarchical and modular networks to host complex dynamical regimes, that is, when nodes are neither fully independent nor fully synchronized. We characterize this behaviour by introducing a measure of functional complexity.

Speaker
Maxi San MIguel

Description I will address the general issue of how collective social phenomena can be studied from a physicist´s perspective on interactions and on the use of models and data. I will consider social consensus as a paradigmatic problem, and I will discuss what can be learnt about this problem from the simple voter model that accounts for the mechanism of social imitation. I will also discuss what properties of the social network of interactions are relevant and what are irrelevant to reach consensus. Finally I will show how a metapopulation voter model properly describes the statistical regularities and spatial correlations found in US presidential electoral data. The model uses as input parameters census data on spatially distributed population and its mobility.

Speaker
Tiago Simas

Description Background: Semi-metric analysis studies the topological features of weighted mathematical relations and has been employed in many areas of complex networks, such as extracting knowledge from documents, predicting social behavior and so on. In this work semi-metric analysis was applied to the human brain connectome and specifically to assess the sensitivity and specificity of the technique in distinguishing adolescents with Autism Spectrum Condition (ASC) and Major Depressive Disorders (MDD) from their typically developing peers. Methods: Blood-oxygenation level dependent sensitive functional MRI data were acquired without the presence of an active task (i.e. passive rest). Weighted relations (networks) were derived from time-series correlations between brain regions. Subsequently, semi-metric measures were obtained that characterise the specialization and dispersion of communicability across the brain, as well as the strength of specialized or dispersed co-activity. Case-control differences were tested in terms of global and local semi-metricity. The inter-hemispheric relationship of semi-metricity was also examined. Results: This topological analysis of the human connectome identified: (1) relative to typically developing adolescents, participants with MDD and ASC had opposing directions of global specialization (increased in MDD) and dispersion (increased in ASC); (2) local regions of the brain where autism and depression differ from controls; (3) hemisphere lateralization effects, and finally; (4) give some evidence in support of findings that autism and depression are in opposite extremes of psychiatric disorders.

Speaker
Daniele Quercia

Description For the last year or so, we have been working on studying social media in the context of London. By combining what Twitter users in a variety of London neighborhoods talk about with census data, we showed that certain topics are correlated (positively and negatively) with neighborhood deprivation. Users in more deprived neighborhoods tweet about wedding parties, matters expressed in Spanish/Portuguese, and celebrity gossips. By contrast, those in less deprived neighborhoods tweet about vacations, professional use of social media, environmental issues, sports, and health issues. More recently, we launched two crowdsourcing websites. First, we launched urbanopticon.org, which extracts Londoners' mental images of the city. By testing which places are remarkable and unmistakable and which places represent faceless sprawl, we are able to draw the recognizability map of London [1,2]. The site has attracted tens of thousands of players, and I will show you the results published in WWW this year. The second site is called urbangems.org. This crowdsources visual perceptions of quiet, beauty and happiness across the city using Google Street View pictures. The aim is to identify the visual cues that are generally associated with concepts difficult to define such beauty, happiness, quietness, or even deprivation [3,4]. The site has been awarded the A.T. Kearney Prize and has been featured in falling-walls.com 2012 in Berlin. [1] Look familiar? http://bit.ly/HgvqZ7 [2] Psychological Maps 2.0: A web engagement enterprise starting in London. WWW 2013 http://bit.ly/189AzfL [3] Project aims to crowdsource what makes a happy city http://bbc.in/15WMnI9 [4] Aesthetic Capital: What Makes London Look Beautiful, Quiet, and Happy? CSCW 2014 http://bit.ly/19NTEr6