History of Chemistry of Materials According to Topic Evolution Based on Network Analysis and Natural Language Processing

Author(s)

Brito, Ana Caroline M. ; Oliveira, Maria Cristina F. ; Oliveira Jr, Osvaldo N. ; Silva, Filipi N. ; Amancio, Diego R.

• Document type: Journal article
• Source: CHEMISTRY OF MATERIALS; v. 36, n. 1, p. 7-pg., 2024-01-09.

Abstract

Chemistry of Materials has a rich history of service to the research community investigating materials with emphasis on their chemical properties and the varied methodologies applicable to producing them. In this editorial, we wish to celebrate the journal's 35th anniversary by revisiting this history identifying the topics that were the most relevant (or frequent) in the publications along more than three decades. This is performed with computational tools from network analysis and natural language processing, which is an area of artificial intelligence. The outputs of these history accounts are citation networks with well-defined communities that refer to the relevant topics since the beginning of the journal. We hope that the readers familiar with Chemistry of Materials will appreciate a history produced from the perspective of automated tools. (AU)

• FAPESP's process: 18/22214-6 - Towards a convergence of technologies: from sensing and biosensing to information visualization and machine learning for data analysis in clinical diagnosis
• Grantee: Osvaldo Novais de Oliveira Junior
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 20/06271-0 - Combining complex networks and word embeddings in text classification tasks
• Grantee: Diego Raphael Amancio
• Support Opportunities: Regular Research Grants
• FAPESP's process: 20/14817-2 - Using complex networks and natural language processing to characterize and predict academic success
• Grantee: Ana Caroline Medeiros Brito
• Support Opportunities: Scholarships in Brazil - Doctorate