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RelPath: an interactive tool to visualize branches of studies and quantify the expertise of authors by citation paths

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Abstract

Networks of scientific publications play a fundamental role in the search for relevant papers to a specific research topic, as well as in finding authors with expertise in different branches of study. Making a selection of the most important references of a specific paper to understand the evolution of a branch of study is an essential task in the academic world. A challenge for the scientific community has been to identify possible authors relevant to a target paper, for example, to select them as potential reviewers. A solution to find potential expert candidates can be based on the network of citations and on how relevant the authors of selecting papers are in relation to the target paper. With the motivation for developing interactive visual software that helps both researchers and editorial committees, in this paper we present RelPath, a system to help with the task of finding relevant papers and authors for a selected paper. RelPath includes the submission paper in a citations network and establishes relevance of the edges in the network, through which it is possible to build branches of studies and establish a ranking of authors. In this work, we introduce an index to quantify the expertise of the authors by citation paths and we propose a collaborative method to ranking references.

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Notes

  1. Considering abstract, title, and keyword as the corpus for each document.

  2. NoSQL(not only SQL) is a class of database management systems (DBMS).

  3. ‘Marching cubes’ is a computer graphic topic on the extraction of isosurfaces.

  4. https://scholar.google.com.

  5. Information provided by Google Scholar, December 22, 2019.

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Correspondence to Orlando Fonseca Guilarte.

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Guilarte, O.F., Barbosa, S.D.J. & Pesco, S. RelPath: an interactive tool to visualize branches of studies and quantify the expertise of authors by citation paths. Scientometrics 126, 4871–4897 (2021). https://doi.org/10.1007/s11192-021-03959-2

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