The last Ebola outbreak (2014) in West Africa shown again the huge problems caused by this virus. Despite of the enormous numbers of infected and fatal cases, this wasn’t the first crisis related to this disease. Before this, it was registered at least six others crisis involving more than one hundred deaths. Over the years, and during these different crisis, namely between 1977 and 2016, the scientific community have published 3871 papers, softwares, revisions, book chapters and other kinds of works from a very diversified knowledge field, that were indexed on the Web of Knowledge platform with the name “Ebola” on the title.
The aim of this work is to show and discuss some analytical methodologies on social networks analysis, that are potentially capable to describe the behavior of Ebola related knowledge networks, over the time, highlighting the periods of outbreaks. It has considered the institution nationality of the author and co-author on each publication. Among the different indicators analyzed, the Self-Loops and the Average Geodesic Distance showed the most interesting results. A non-directional network was structured on NodeXL software, including the first author as Vertex1 (repeating this by the number of connected partners) and the co-authors as Vertex2. The Self-Loops indicated how many times the first author links to co-authors institutions of the same country. This indicator was compared to the total edge and to the total number of publications produced on the same period. Comparing the Self-Loops and the total edges on ten different periods, considering epidemiological crisis and non-crisis periods, in the 1990’s decade it was observed an intensive reduction of the self-loops weight compared to the total number of connections. This result may point that, on that moment, the scientific knowledge production ecosystem of Ebola were geographically more diversified if compared to the others periods after and before. On the other hand, on the last decade, the Self-Loops became bigger. Comparing this same indicator with the total indexed scientific publications, looking for the same periods, it was observed that the average of Self-Loops on each work grown up on a relatively constant way over the years, starting on 0,75 in the 1970s, going to 1,44 in 2002-2004 period and reaching to 2,20 in the last period (2014-2016). These data can point that, over the years, each publication further valorized the endogenous knowledge, even if it seeks distant partnerships. This distant partnership become clear when, observing the network Maximum Geodesic Distance, as well as the Average Geodesic Distance. It’s possible to verify that in both cases there was an increase in values over the year, indicating that the networks that compose the Ebola related knowledge production ecosystem becomes wider. In this sense, is possible to observe that the social network analysis methodologies introduce indicators that tend to reflect the scientific community behavior in front of Ebola.