Associations between author-level metrics in subsequent time periods

Autor(es)

Brito, Ana C. M. ^[1] ; Silva, Filipi N. ^[2] ; Amancio, Diego R. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Inst Math & Comp Sci, Sao Carlos - Brazil

^[2] Indiana Univ, Network Sci Inst, Bloomington, IN 47408 - USA

• Tipo de documento: Artigo Científico
• Fonte: Journal of Informetrics; v. 15, n. 4 NOV 2021.
• Citações Web of Science: 0

Resumo

Understanding the dynamics of authors is relevant to predict and quantify performance in science. While the relationship between recent and future citation counts is well-known, many relationships between scholarly metrics at the author-level remain unknown. In this context, we performed an analysis of author-level metrics extracted from subsequent periods, focusing on visibility, productivity and interdisciplinarity. First, we investigated how metrics controlled by the authors (such as references diversity and productivity) affect their visibility and citation diversity. We also explore the relationship between authors' interdisciplinarity and citation counts. The analysis on a subset of Physics papers revealed that there is no strong correlation between authors' productivity and future visibility for most of the authors. A higher fraction of strong positive correlations though was found for those with a lower number of publications. We also found that reference diversity computed at the author-level may impact positively authors' future visibility. The analysis of metrics impacting future interdisciplinarity suggests that productivity may play a role only for low-productivity authors. We also found a surprisingly strong positive correlation between references diversity and interdisciplinarity, suggesting that an increase in diverse citing behavior may be related to a future increase in authors interdisciplinarity. Finally, interdisciplinarity and visibility were found to be positively associated, with moderate correlations. Significant positive correlations were observed for 24% of authors with lower productivity. (AU)

• Processo FAPESP: 20/06271-0 - Combinando redes complexas e word embeddings em tarefas de classificação de textos
• Beneficiário: Diego Raphael Amancio
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 20/14817-2 - Usando redes complexas e processamento de línguas naturais para caracterização e previsão de sucesso na Ciência
• Beneficiário: Ana Caroline Medeiros Brito
• Modalidade de apoio: Bolsas no Brasil - Doutorado