Papers by Bruno Goncalves
BMC Infectious Diseases, 2011
Background: Computational models play an increasingly important role in the assessment and contro... more Background: Computational models play an increasingly important role in the assessment and control of public health crises, as demonstrated during the 2009 H1N1 influenza pandemic. Much research has been done in recent years in the development of sophisticated data-driven models for realistic computer-based simulations of infectious disease spreading. However, only a few computational tools are presently available for assessing scenarios, predicting epidemic evolutions, and managing health emergencies that can benefit a broad audience of users including policy makers and health institutions. Results: We present "GLEaMviz", a publicly available software system that simulates the spread of emerging human-to-human infectious diseases across the world. The GLEaMviz tool comprises three components: the client application, the proxy middleware, and the simulation engine. The latter two components constitute the GLEaMviz server. The simulation engine leverages on the Global Epidemic and Mobility (GLEaM) framework, a stochastic computational scheme that integrates worldwide high-resolution demographic and mobility data to simulate disease spread on the global scale. The GLEaMviz design aims at maximizing flexibility in defining the disease compartmental model and configuring the simulation scenario; it allows the user to set a variety of parameters including: compartment-specific features, transition values, and environmental effects. The output is a dynamic map and a corresponding set of charts that quantitatively describe the geo-temporal evolution of the disease. The software is designed as a client-server system. The multi-platform client, which can be installed on the user's local machine, is used to set up simulations that will be executed on the server, thus avoiding specific requirements for large computational capabilities on the user side. Conclusions: The user-friendly graphical interface of the GLEaMviz tool, along with its high level of detail and the realism of its embedded modeling approach, opens up the platform to simulate realistic epidemic scenarios. These features make the GLEaMviz computational tool a convenient teaching/training tool as well as a first step toward the development of a computational tool aimed at facilitating the use and exploitation of computational models for the policy making and scenario analysis of infectious disease outbreaks.
We present a complete analytical solution of a system of Potts spins on a random k-regular graph ... more We present a complete analytical solution of a system of Potts spins on a random k-regular graph in both the canonical and microcanonical ensembles, using the Large Deviation Cavity Method (LDCM). The solution is shown to be composed of three different branches, resulting in a non-concave entropy function.
Background On 11 June the World Health Organization officially raised the phase of pandemic alert... more Background On 11 June the World Health Organization officially raised the phase of pandemic alert (with regard to the new H1N1 influenza strain) to level 6. As of 19 July, 137,232 cases of the H1N1 influenza strain have been officially confirmed in 142 different countries, and the pandemic unfolding in the Southern hemisphere is now under scrutiny to gain insights about the next winter wave in the Northern hemisphere.
Abstract Online social networking communities may exhibit highly complex and adaptive collective ... more Abstract Online social networking communities may exhibit highly complex and adaptive collective behaviors. Since emotions play such an important role in human decision making, how online networks modulate human collective mood states has become a matter of considerable interest.
Abstract We examine the properties of all HTTP requests generated by a thousand undergraduates ov... more Abstract We examine the properties of all HTTP requests generated by a thousand undergraduates over a span of two months. Preserving user identity in the data set allows us to discover novel properties of Web traffic that directly affect models of hypertext navigation. We find that the popularity of Web sites--the number of users who contribute to their traffic--lacks any intrinsic mean and may be unbounded.
Abstract Micro-blogging systems such as Twitter expose digital traces of social discourse with an... more Abstract Micro-blogging systems such as Twitter expose digital traces of social discourse with an unprecedented degree of resolution of individual behaviors. They offer an opportunity to investigate how a large-scale social system responds to exogenous or endogenous stimuli, and to disentangle the temporal, spatial and topical aspects of users' activity. Here we focus on spikes of collective attention in Twitter, and specifically on peaks in the popularity of hashtags.
The last decade saw the advent of increasingly realistic epidemic models that leverage on the ava... more The last decade saw the advent of increasingly realistic epidemic models that leverage on the availability of highly detailed census and human mobility data. Data-driven models aim at a granularity down to the level of households or single individuals. However, relatively little systematic work has been done to provide coupled behavior-disease models able to close the feedback loop between behavioral changes triggered in the population by an individual's perception of the disease spread and the actual disease spread itself.
Abstract: Analysis of aggregate Web traffic has shown that PageRank is a poor model of how people... more Abstract: Analysis of aggregate Web traffic has shown that PageRank is a poor model of how people actually navigate the Web. Using the empirical traffic patterns generated by a thousand users over the course of two months, we characterize the properties of Web traffic that cannot be reproduced by Markovian models, in which destinations are independent of past decisions.
Epitaxial growth has been the focus of much interest in the past years. This interest is derived ... more Epitaxial growth has been the focus of much interest in the past years. This interest is derived mainly from the fact that these kinds of processes have numerous applications 1–3 in developing new types of devices and materials with some special characteristics. Among these processes, there is one type of growth characterized by the presence of longrange elastic interactions that play a special role 4.
Abstract: We present a contribution to the debate on the predictability of social events using bi... more Abstract: We present a contribution to the debate on the predictability of social events using big data analytics. We focus on the elimination of contestants in the American Idol TV shows as an example of a well defined electoral phenomenon that each week draws millions of votes in the USA. We provide evidence that Twitter activity during the time span defined by the TV show airing and the voting period following it, correlates with the contestants ranking and allows the anticipation of the voting outcome.
Abstract. The recently proposed hysteretic optimization (HO) procedure is applied to the 1D Ising... more Abstract. The recently proposed hysteretic optimization (HO) procedure is applied to the 1D Ising spin chain with long range interactions. To study its effectiveness, the quality of ground state energies found as a function of the distance dependence exponent, σ, is assessed. It is found that the transition from an infinite range to a long range interaction at σ= 0.5 is accompanied by a sharp decrease in the performance.
Abstract: Large scale analysis and statistics of socio-technical systems that just a few short ye... more Abstract: Large scale analysis and statistics of socio-technical systems that just a few short years ago would have required the use of consistent economic and human resources can nowadays be conveniently performed by mining the enormous amount of digital data produced by human activities. Although a characterization of several aspects of our societies is emerging from the data revolution, a number of questions concerning the reliability and the biases inherent to the big data" proxies" of social life are still open.
Abstract We examine partisan differences in the behavior, communication patterns and social inter... more Abstract 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.
Complex networks have proved to be useful tools to explore natural or man-made phenomena as diver... more Complex networks have proved to be useful tools to explore natural or man-made phenomena as diverse as the Internet 1, human societies 2, transport patterns between airports 3, 4, or even metabolic reactions in the interior of cells 5. The vertices in the networks represent the elements of the system and the edges the interactions between them. The study of the topology of the network provides valuable information on how the basic components interact 6–8.
Access to the Internet has become increasingly popular during the past decade. However, despite i... more Access to the Internet has become increasingly popular during the past decade. However, despite its importance, much is still unknown about the intrinsic properties of the Web, the way people interact with it, and how it impacts our culture 1–4. Several theoretical approaches have been proposed in the past few years 5–12, but some fundamental issues are yet to be fully understood.
Abstract Online social media are complementing and in some cases replacing person-to-person socia... more Abstract Online social media are complementing and in some cases replacing person-to-person social interaction and redefining the diffusion of information. In particular, microblogs have become crucial grounds on which public relations, marketing, and political battles are fought. We demonstrate a web service that tracks political memes in Twitter and helps detect astroturfing, smear campaigns, and other misinformation in the context of US political elections.
Background Computational models play an increasingly important role in the assessment and control... more Background Computational models play an increasingly important role in the assessment and control of public health crises, as demonstrated during the 2009 H1N1 influenza pandemic. Much research has been done in recent years in the development of sophisticated data-driven models for realistic computer-based simulations of infectious disease spreading.
Abstract The widespread adoption of social media for political communication creates unprecedente... more Abstract The widespread adoption of social media for political communication creates unprecedented opportunities to monitor the opinions of large numbers of politically active individuals in real time. However, without a way to distinguish between users of opposing political alignments, conflicting signals at the individual level may, in the aggregate, obscure partisan differences in opinion that are important to political strategy.
Analysis of aggregate and individual Web requests shows that PageRank is a poor predictor of traf... more Analysis of aggregate and individual Web requests shows that PageRank is a poor predictor of traffic. We use empirical data to characterize properties of Web traffic not reproduced by Markovian models, including both aggregate statistics such as page and link traffic, and individual statistics such as entropy and session size.
Abstract Analysis has shown that the standard Markovian model of Web navigation is a poor predict... more Abstract Analysis has shown that the standard Markovian model of Web navigation is a poor predictor of actual Web traffic. Using empirical data, we characterize several properties of Web traffic that cannot be reproduced with Markovian models but can be explained by an agent-based model that adds several realistic browsing behaviors. First, agents maintain bookmark lists used as teleportation targets.
Uploads
Papers by Bruno Goncalves