A Computational Approach for Identifying Keywords Related to the 2030 Agenda for Sustainable Development Goals in a Brazilian Higher Education Institution

Over the past few years, there has been a need to discuss the strengthening of academic contributions to the 2030 Agenda as a vital facilitator for planning and evaluating sustainable goals. However, managing information in this field has become an internal institutional challenge for higher educati...

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Main Authors: Ana Carolina Estorani Polessa, Gisele Goulart Tavares, Ruan Medina, Camila Martins Saporetti, Tiago Silveira Gontijo, Matteo Bodini, Leonardo Goliatt, Priscila Capriles
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Societies
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Online Access:https://www.mdpi.com/2075-4698/15/6/165
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author Ana Carolina Estorani Polessa
Gisele Goulart Tavares
Ruan Medina
Camila Martins Saporetti
Tiago Silveira Gontijo
Matteo Bodini
Leonardo Goliatt
Priscila Capriles
author_facet Ana Carolina Estorani Polessa
Gisele Goulart Tavares
Ruan Medina
Camila Martins Saporetti
Tiago Silveira Gontijo
Matteo Bodini
Leonardo Goliatt
Priscila Capriles
author_sort Ana Carolina Estorani Polessa
collection DOAJ
description Over the past few years, there has been a need to discuss the strengthening of academic contributions to the 2030 Agenda as a vital facilitator for planning and evaluating sustainable goals. However, managing information in this field has become an internal institutional challenge for higher education organizations. Identifying the aspects of sustainable development goals within research projects is crucial for developing strategies and policies that promote collaboration in joint projects, ultimately strengthening research in SDGs. Recent advancements in computational methods have emerged as powerful tools to address the difficulties associated with utilizing information related to academic contributions to the 2030 Agenda. These methods offer innovative ways to process, analyze, and visualize data, enabling decision-makers to gain valuable insights and make informed decisions. This paper proposes a computational model to facilitate the identification of the 2030 Agenda for Sustainable Development within teaching, research, and extension projects at a Brazilian University. The model aims to align academic research and institutional actions with the 17 Sustainable Development Goals (SDGs) established by the United Nations. The developed model can extract and categorize SDG-related text data by employing keywords and natural language processing techniques. The development of this tool is driven by the need for universities to adapt their curricula and contribute to the 2030 Agenda. The model helps identify the potential impact of projects on the SDGs, assessing the alignment of research or actions with specific goals, and improving data governance. By utilizing the proposed model, educational institutions can efficiently manage their research, organize their work around the SDGs, foster collaboration internally and with external partners, and enhance their internationalization efforts. The model has the potential to increase the capabilities of educational institutes as vital mobilizing agents, reducing costs and streamlining the analysis of information related to the 2030 Agenda. This, in turn, enables more effective academic actions to integrate sustainable goals.
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spelling doaj-art-a6fd8c81fb83434ebb0f4ff5957937df2025-08-20T03:29:48ZengMDPI AGSocieties2075-46982025-06-0115616510.3390/soc15060165A Computational Approach for Identifying Keywords Related to the 2030 Agenda for Sustainable Development Goals in a Brazilian Higher Education InstitutionAna Carolina Estorani Polessa0Gisele Goulart Tavares1Ruan Medina2Camila Martins Saporetti3Tiago Silveira Gontijo4Matteo Bodini5Leonardo Goliatt6Priscila Capriles7Social Sciences Graduate Program, Federal University of Juiz de Fora, Juiz de Fora 36036-900, MG, BrazilComputational Modeling Graduate Program, Federal University of Juiz de Fora, Juiz de Fora 36036-900, MG, BrazilComputational Modeling Graduate Program, Federal University of Juiz de Fora, Juiz de Fora 36036-900, MG, BrazilDepartment of Computational Modeling, Polytechinic Institute, Rio de Janeiro State University, Nova Friburgo 22000-900, RJ, BrazilFederal University of São João del-Rei, Campus Centro Oeste, Divinópolis 355901-296, MG, BrazilDipartimento di Economia, Management e Metodi Quantitativi, Università degli Studi di Milano, Via Conservatorio 7, 20122 Milano, ItalyDepartment of Applied and Computational Mechanics, Federal University of Juiz de Fora, Juiz de Fora 36036-900, MG, BrazilDepartment of Computer Science, Federal University of Juiz de Fora, Juiz de Fora 36036-900, MG, BrazilOver the past few years, there has been a need to discuss the strengthening of academic contributions to the 2030 Agenda as a vital facilitator for planning and evaluating sustainable goals. However, managing information in this field has become an internal institutional challenge for higher education organizations. Identifying the aspects of sustainable development goals within research projects is crucial for developing strategies and policies that promote collaboration in joint projects, ultimately strengthening research in SDGs. Recent advancements in computational methods have emerged as powerful tools to address the difficulties associated with utilizing information related to academic contributions to the 2030 Agenda. These methods offer innovative ways to process, analyze, and visualize data, enabling decision-makers to gain valuable insights and make informed decisions. This paper proposes a computational model to facilitate the identification of the 2030 Agenda for Sustainable Development within teaching, research, and extension projects at a Brazilian University. The model aims to align academic research and institutional actions with the 17 Sustainable Development Goals (SDGs) established by the United Nations. The developed model can extract and categorize SDG-related text data by employing keywords and natural language processing techniques. The development of this tool is driven by the need for universities to adapt their curricula and contribute to the 2030 Agenda. The model helps identify the potential impact of projects on the SDGs, assessing the alignment of research or actions with specific goals, and improving data governance. By utilizing the proposed model, educational institutions can efficiently manage their research, organize their work around the SDGs, foster collaboration internally and with external partners, and enhance their internationalization efforts. The model has the potential to increase the capabilities of educational institutes as vital mobilizing agents, reducing costs and streamlining the analysis of information related to the 2030 Agenda. This, in turn, enables more effective academic actions to integrate sustainable goals.https://www.mdpi.com/2075-4698/15/6/165sustainable development goalsnatural language processingcomputational toolseducationinnovative methodologies
spellingShingle Ana Carolina Estorani Polessa
Gisele Goulart Tavares
Ruan Medina
Camila Martins Saporetti
Tiago Silveira Gontijo
Matteo Bodini
Leonardo Goliatt
Priscila Capriles
A Computational Approach for Identifying Keywords Related to the 2030 Agenda for Sustainable Development Goals in a Brazilian Higher Education Institution
Societies
sustainable development goals
natural language processing
computational tools
education
innovative methodologies
title A Computational Approach for Identifying Keywords Related to the 2030 Agenda for Sustainable Development Goals in a Brazilian Higher Education Institution
title_full A Computational Approach for Identifying Keywords Related to the 2030 Agenda for Sustainable Development Goals in a Brazilian Higher Education Institution
title_fullStr A Computational Approach for Identifying Keywords Related to the 2030 Agenda for Sustainable Development Goals in a Brazilian Higher Education Institution
title_full_unstemmed A Computational Approach for Identifying Keywords Related to the 2030 Agenda for Sustainable Development Goals in a Brazilian Higher Education Institution
title_short A Computational Approach for Identifying Keywords Related to the 2030 Agenda for Sustainable Development Goals in a Brazilian Higher Education Institution
title_sort computational approach for identifying keywords related to the 2030 agenda for sustainable development goals in a brazilian higher education institution
topic sustainable development goals
natural language processing
computational tools
education
innovative methodologies
url https://www.mdpi.com/2075-4698/15/6/165
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