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

被引:1
|
作者
Brito, Ana Caroline M.
Oliveira, Maria Cristina F.
Oliveira Jr, Osvaldo N.
Silva, Filipi N.
Amancio, Diego R.
机构
[1] Institute of Mathematical Sciences and Computing, University of São Paulo, São Paulo, São Carlos
[2] São Carlos Institute of Physics, University of São Paulo, São Paulo, Sao Carlos
[3] Observatory on Social Media, Indiana University, Bloomington, 47408, IN
基金
巴西圣保罗研究基金会;
关键词
D O I
10.1021/acs.chemmater.3c02962
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
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.
引用
收藏
页码:1 / 7
页数:7
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