REALM: A Computational Framework for Investigating Research Impacts Through Alternative Metrics

• Luiz Fernando Monsores Passos Maia Federal University of Rio de Janeiro
• Jonice Oliveira Federal University of Rio de Janeiro https://orcid.org/0000-0002-2495-1463

DOI: https://doi.org/10.5753/sbbd.2018.22217

Abstract

In some emergency scenarios or undefined domains, more collaboration among specialists is required. For instance, we can mention the Zika virus, whose epidemic potential became evident in 2014. In Brazil, it had a high occurrence rate, affecting thousands of people and causing overcrowding of public and private emergency services. The social media has been used as the primary alternative to exchange information and create scientific knowledge. The researchers and physicians use social media to communicate their discoveries - abdicating of official and scientific publications - because they needed a faster and proactive way to exchange knowledge. This scenario demands mechanisms to identify experts and to recognize how citizens interpret the efficiency of professionals and their efforts to find solutions. For this purpose, we created a computational framework to identify the social reputation of a researcher or a study, based on alternative impact metrics (altmetrics). To evaluate this framework, we did a Proof of Concept in the Zika context.

Keywords: Pandemic, social media, social reputation, altmetrics, analytics and ranking

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