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Author and Keyword Bursts as Indicators for the Identification of Emerging or Dying Research Trends

Patrick Kenekayoro1★★ Corresponding author

  1. 1Niger Delta University Address Mathematics / Computer Science Department Niger Delta University PMB, Amassoma, Bayelsa, NIGERIA.

CORRESPONDENCE

Patrick Kenekayoro

Niger Delta University Address Mathematics / Computer Science Department Niger Delta University PMB, Amassoma, Bayelsa, NIGERIA.

patrick.kenekayoro@outlook.com

Received: 03-05-2020; Revised: 03-07-2020; Accepted: 19-07-2020.

Volume 9, Issue 2 · pp. 120–126 · PUBLISHED · DOI: 10.5530/jscires.9.2.15

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ABSTRACT

Context: Identifying emerging research fronts is critical as it aids policy makers or funding agencies on their decisions in research policies, it is also a useful tool for guiding young researchers’ research direction. Studies have successfully used techniques such as co-citation and co-word analysis of data retrieved from ISI databases to investigate emerging or dying research trends. Aim: With the advent of publicly available preprint databases such as BioRxiv, it becomes necessary to investigate if the state of the art techniques used to identify emerging research areas can be transferred to a dataset extracted from these public archives. Methods and Materials: A cluster analysis of keyword burst and author burst from data extracted from BioRxiv is used to investigate the suitability of BioRxiv dataset for the investigation of emerging or dying research trends. Results: The results showed that although the data retrieved from BioRxiv may not yet be mature enough for reliable analyses, the increased awareness shown in the exponential growth in preprint submissions suggests that this data source will be a valuable resource and the techniques described is this research can be used to discover interesting trends from preprint databases on emerging or dying research fronts.

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    Kenekayoro, P. (). Author and Keyword Bursts as Indicators for the Identification of Emerging or Dying Research Trends. Journal of Scientometric Research, 9(2), 120–126. https://doi.org/10.5530/jscires.9.2.15