Computational Mining on IBICT BDTD’s Thesis and Dissertation Metadata for Supporting Social Science Research

Rodrigo R. Filho; Elismênnia Oliveira; Jordão Nunes; Marcelo Inuzuka; Hugo do Nascimento

doi:10.5753/eniac.2020.12163

Rodrigo R. Filho Universidade Federal de Goias
Elismênnia Oliveira Universidade Federal de Goias
Jordão Nunes Universidade Federal de Goiás
Marcelo Inuzuka Universidade Federal de Goiás
Hugo do Nascimento Universidade Federal de Goiás

DOI: https://doi.org/10.5753/eniac.2020.12163

Resumo

The Brazilian Digital Library of Thesis and Dissertations (BDTD) provides essential data to support many social sciences investigations. Nevertheless, there is still a lack of computation tools tailored for helping extract and analyze the necessary information from the BDTD library. In this paper, we discuss the development of computational solutions to answer questions from a particular social sciences research using metadata from BDTD. The solutions involve the integration of data processing and presentation techniques, such as string-processing algorithms, knowledge graphs and information visualizations. All programming codes implemented at the scope of the project are available for helping other researchers. The paper also highlights the importance of having researchers from Social Science and Computer Science working together, what motivates future collaborations in these areas.

Palavras-chave: Social Science, text analysis, knowledge graphs, information visualization

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