Lab CORES is an initiative of the Universidade Federal do Rio de Janeiro.
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Av. Athos da Silveira Ramos, 274
Ilha da Cidade Universitária
Rio de Janeiro - RJ
Brasil
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PROJECTS
The Impact of the Virtual on the Real: How the Use of Online Social Networks Impacted the COVID-19 Epidemic in Brazil?
Description: More than just entertainment or learning, through social media, we can identify unprecedented levels of citizen engagement and participation. This activity is called "participatory sensing" or "citizen sensing." In participatory sensing, a sensor is not necessarily hardware but can be a virtual sensor or a human interpreting sensory data. Assuming that citizens use social media to report issues, publicize events, express opinions, and transmit information they deem relevant, such information can aid in virtual sensing and create a more accurate understanding of the city. In this project proposal, which spans one year, we aim to compare the impact of COVID-19 in Brazil in the real scenario—such as cases, deaths, vaccination, and social isolation—with the virtual scenario. The primary research question is, "Did engagement on social media reflect or impact the real behavior of Brazilian citizens during the COVID-19 epidemic?". To do this, we will use data from DATASUS and PCDaS (Data Science Platform applied to Health) as sources of "real-world" data and public data from interactions on Twitter, Facebook, and Instagram for mapping interactions in the "virtual world."
Members: Jonice de Oliveira Sampaio - Coordinator, Fabio Porto - Member
[Oracle] Extracting Knowledge from Big Social Data - Special Case: Pandemics & Epidemics
Description: In this project, Big Social Data refers to large data volumes that relate to people interactions (with other people or things) or describe their behaviors, needs, and patterns. So, we define our research question, which is: RQ1: How to manage the massive volume of social data, envisioning the urban sensing, dealing with multiple data streams of varying data types, and different knowledge levels of users during large-scale sanitary crises, especially pandemic and epidemics? The proponent chose two real scenarios to apply this research: COVID-19 and depression.
Members: Jonice de Oliveira Sampaio - Coordinator, Sirius Tadeu da Silva - Member, Luis Fernando Monsores Passos Maia - Member, Diogo Nolasco - Member
[PIBIC] Study and Development of Tools and Services for Collecting Large Volumes of Social Media Data
Description: This work is placed within the technical context, considering the development of competencies related to understanding data analysis, the comprehension of ethical issues involved in data collection, the automation of social media data collection mechanisms aimed at training communicators regarding data analysis, taking as a premise the transparency of the process and the generation of information and its value in communication. This work is focused on building artifacts to be made available as services and tools for anyone interested in extracting and analyzing social media data.
Members: Jonice de Oliveira Sampaio - Coordinator, Tiago França - Member, Camila Lacerda da Silva - Member
[CAPES] Digital Technologies for Monitoring, Mapping, and Controlling Outbreaks, Endemics, Epidemics, and Pandemics
Description: The rapid spread of COVID-19 in the country and the high lethality of confirmed cases are causing great concern and suffering in the population and can lead to a collapse in healthcare services. It is essential, for the effective control of the disease, to understand its space-time diffusion process and its social determinants. Furthermore, knowledge of the magnitude of the epidemic process will support proper planning of healthcare actions for COVID-19 patients. Reducing the growth rate of the disease ("flattening the curve") is an essential goal to be achieved through social isolation, along with forecasting hospital and personnel resources, developing guidelines and public policies for cities and regions of the country, and guiding the appropriate time for the gradual return of social and economic activities. To achieve these objectives, it is essential to collect and process numerous pieces of information that can also determine whether the coping policies adopted are effective, their impact on virus spread, and the timing of returning to activities. However, the impact of the epidemic varies among individuals from different social groups in terms of socioeconomic conditions, ethnic-racial relations, and gender. It is important to consider this information in the analysis, as the correlation of these data with other information collected by state agencies, public hospitals, and universities can identify relevant patterns. A major challenge for coping with the epidemic from the epidemiological modeling standpoint is obtaining reliable information regarding the date of symptoms, symptom severity, case reporting, among various other types of information. In this context, different data sources, including health system data, mobility data, and others, must be aggregated into an integrated repository so that they can be accessed by different research groups in this proposal and by the SUS (Brazilian Unified Health System). This integrated database is already being organized by the Modeling Working Group (GT) at UFRJ. It is essential for generating an innovation ecosystem in conjunction with the full use of data science and AI resources to combat the COVID-19 pandemic. This ever-increasing volume of data requires infrastructure and specific techniques to be adequately processed, making AI, Big Data, Internet of Things, and other instruments that contribute to digital transformation essential in the field of healthcare. One technology influences the other and can even expand its meaning. The combination of different datasets may have varying relevance depending on the source that seeks to understand what they represent, whether it is healthcare organizations, civil society, a specific level of government, and especially research groups that promote Open Science and Open Data.
Members: Guilherme Horta Travassos - Coordinator, Jonice de Oliveira Sampaio - Member
Scientific Cooperation UFRJ and UEVE/Paris Saclay
Description: Scientific cooperation agreement aiming to contribute to Brazilian research between UFRJ, through the Department of Computer Science, and the Université d "Évry-Val-d" Essonne (UEVE)/Paris Saclay, through COSMO/IBISC. The research will be in the area of Social Computing, Security, Privacy, and Semantic Web.
Members: Jonice de Oliveira Sampaio - Coordinator, Thiago Moreira - Member, Nazim Agoulmine - Member