Topological-collaborative approach for disambiguating authors' names in collaborative networks

Autor(es)

Amancio, Diego R. ^[1] ; Oliveira, Jr., Osvaldo N. ^[2] ; Costa, Luciano da F. ^[2]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Inst Math & Comp Sci, BR-13560970 Sao Carlos, SP - Brazil

^[2] Univ Sao Paulo, Sao Carlos Inst Phys, BR-13560970 Sao Carlos, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: SCIENTOMETRICS; v. 102, n. 1, p. 465-485, JAN 2015.
• Citações Web of Science: 6

Resumo

Concepts and methods of complex networks have been employed to uncover patterns in a myriad of complex systems. Unfortunately, the relevance and significance of these patterns strongly depends on the reliability of the datasets. In the study of collaboration networks, for instance, unavoidable noise pervading collaborative networks arises when authors share the same name. To address this problem, we derive a hybrid approach based on authors' collaboration patterns and topological features of collaborative networks. Our results show that the combination of strategies, in most cases, performs better than the traditional approach which disregards topological features. We also show that the main factor accounting for the improvement in the discriminability of homonymous authors is the average shortest path length. Finally, we show that it is possible to predict the weighting associated to each strategy compounding the hybrid system by examining the discrimination obtained from the traditional analysis of collaboration patterns. Because the methodology devised here is generic, our approach is potentially useful to classify many other networked systems governed by complex interactions. (AU)

• Processo FAPESP: 10/00927-9 - Classificação de textos com redes complexas
• Beneficiário: Diego Raphael Amancio
• Linha de fomento: Bolsas no Brasil - Doutorado Direto
• Processo FAPESP: 11/50761-2 - Modelos e métodos de e-Science para ciências da vida e agrárias
• Beneficiário: Roberto Marcondes Cesar Junior
• Linha de fomento: Auxílio à Pesquisa - Temático
• Processo FAPESP: 13/06717-4 - Modelagem do conhecimento e comportamento com redes complexas
• Beneficiário: Diego Raphael Amancio
• Linha de fomento: Bolsas no Brasil - Pós-Doutorado