Key Author Analysis in Research Professionals’ Relationship Network Using Citation Indices and Centrality

Abstract

In social network analysis, the importance of an actor can be found by using the centrality metrics. There are many centrality metrics available e.g. degree, closeness, betweenness, eigenvector etc. In research community authors forms a social network, which is called Research Professionals’ Collaboration Network. This is similar to social network where each author is an actor and an article written together by some authors establishes collaboration between them. Each author acquires a certain value based on the citation of their articles. There are many citation indices are available such as citation count, h-index, g-index, i10-index etc. To analyze the Research Professionals’ collaboration Network and for finding the key author, the citation indices can be used. In this paper, we compare and combine both social network analysis metrics and the citation indices to get better result in finding the key author.

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No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 27 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.