Marcelo Tibau

It was set to keep tabs on the Covid-19 spreading in Brazil

Source: OPAS.

At the start of Covid-19 pandemic, as most people in the world I suppose, I became pretty worried and anxious regarding its outcome. Being a data scientist, I initially used my skills to predict its spreading. I devised a predictive modeling based on Taylor series using the first and second derivatives of the continuous approximation of the usage data. The reason to use this method was due to the shortage of data at the time regarding the virus’s spreading pattern.

During a few months I got a decent forecast (you can check the report that I kept at the time on my personal blog here). Despite that I decided to discontinue the model at the time due a lack of emotional strength — I felt like a sort of Nostradamus at the time, foreboding doom, though I kept a daily update of the number of cases and deaths.

Anyway, there is always a time to call it a day, and for months I couldn’t decide how to call this shot. So, I decided to keep it going until I had access to daily updates. During most of the pandemic, the Brazilian press created a media consortium to consolidate the total of cases and deaths, since the Brazilian government at the time decided to withhold this information.

The consortium disbanded on January 28, 2023 after more than 80% of the population was fully vaccinated and the cases and deaths reached a stability. In this sense, I decided to consolidate the dataset and make it public. Anyone can have access to it at my GitHub repo (https://github.com/marcelo-tibau/covid-19). It was a long journey, but I confess that I am neither relieved nor satisfied. Maybe because it was a daily routine to retrieve the data for more than a 1,000 days or because I still hold my horses regarding the pandemic. Anyway, I hope sooner than later we all could sign in relief and breath undaunted as this pandemic becomes part of History books.

For a portuguese version, read at Update or Die.

You can also read it (or listen it) at:

My new research paper published at Library & Information Science Research.

Marcelo Tibau, Sean Wolfgand Matsui Siqueira, Bernardo Pereira Nunes, Accounting for the knowledge gained during a web search: An empirical study on learning transfer indicators, Library & Information Science Research, Volume 45, Issue 1, 2023, 101222, ISSN 0740-8188, https://doi.org/10.1016/j.lisr.2022.101222. (https://www.sciencedirect.com/science/article/pii/S0740818822000858).

Abstract: Searches with learning intent typically require the users to interact with the searching environment and perform knowledge acquisition features such as scan, read, and process the online content to fulfill their information needs. To capture indicators from searching behaviors that could account for the knowledge gained during a Web search, a qualitative study was performed using the Concurrent Think-Aloud protocol to observe the mechanisms of transfer and map knowledge flows during 78 search sessions. Findings indicate evidence of transfer of learning in the form of sixteen online information searching strategy indicators. This research aids the understanding of how knowledge is gained during search sessions and how to identify behaviors that could indicate that learning has occurred, which could be used to represent knowledge gain on Web search engines. In this way, it can aid search engines to become not only better tools of searching, but also tools of learning.

Keywords: Constant comparative method; Concurrent think-aloud protocol; Transfer of learning; Knowledge gain; Web searching.

To get access to the article, use the share link: https://authors.elsevier.com/a/1gRKl2eSLIkd3Q

#research #informationscience #learning #searchengines