Measuring Interdisciplinarity: A Graph-Based Analysis of Brazilian Academic Committees

This study presents a scientometric analysis of interdisciplinary scientific collaboration in the composition of academic committees in Brazil. The research employed an extensive dataset, obtained from CAPES and Sucupira platforms, which store information on Brazilian academic output: master's and doctoral dissertations and theses. The collected data enabled the examination of relationships between 66 Knowledge Areas (KAs). Applying graphs to model the relationships among committee members, we distinguished each member according to their assigned role: candidate, evaluator, advisor. Three "academic graphs" were designed to represent these relationships: evaluations, invitations, and co-participations. As a method, we adapted a Knowledge Discovery in Database (KDD) process, systematizing the necessary steps to enable the desired measurement. Applying statistical techniques, the research results revealed significant patterns of interdisciplinarity in the composition of the committees. It was possible to identify KAs that collaborate more frequently (Ecology, Education, Linguistics, Zoology), as well as those that demonstrate less interaction, in addition to the relative role of each as a hub for other areas (Biochemistry, Education, Chemistry, and Sociology). This study contributes to a deeper understanding of the role of defense committees in the advancement of Brazilian science, emphasizing the relevance of interdisciplinary collaboration in the evaluation of academic output.

Authors

Institutions

Publication Details

Journal
INFONOMY
Published
2025-05-29
DOI
https://doi.org/10.3145/infonomy.25.018
Primary Topic
University-Industry-Government Innovation Models
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Measuring Interdisciplinarity: A Graph-Based Analysis of Brazilian Academic Committees

Victor Alexandre Ploeger Mansueli, Jesús Pascual Mena‐Chalco
INFONOMY
University-Industry-Government Innovation Models
article

Measuring Interdisciplinarity: A Graph-Based Analysis of Brazilian Academic Committees

Victor Alexandre Ploeger Mansueli, Jesús Pascual Mena‐Chalco
article en

Abstract

This study presents a scientometric analysis of interdisciplinary scientific collaboration in the composition of academic committees in Brazil. The research employed an extensive dataset, obtained from CAPES and Sucupira platforms, which store information on Brazilian academic output: master's and doctoral dissertations and theses. The collected data enabled the examination of relationships between 66 Knowledge Areas (KAs). Applying graphs to model the relationships among committee members, we distinguished each member according to their assigned role: candidate, evaluator, advisor. Three "academic graphs" were designed to represent these relationships: evaluations, invitations, and co-participations. As a method, we adapted a Knowledge Discovery in Database (KDD) process, systematizing the necessary steps to enable the desired measurement. Applying statistical techniques, the research results revealed significant patterns of interdisciplinarity in the composition of the committees. It was possible to identify KAs that collaborate more frequently (Ecology, Education, Linguistics, Zoology), as well as those that demonstrate less interaction, in addition to the relative role of each as a hub for other areas (Biochemistry, Education, Chemistry, and Sociology). This study contributes to a deeper understanding of the role of defense committees in the advancement of Brazilian science, emphasizing the relevance of interdisciplinary collaboration in the evaluation of academic output.

INFONOMYVol. 3(3)
Universidade Federal do ABC (BR)
Openalex Percentile: Top 84%
University-Industry-Government Innovation Models
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.