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Journal of Data and Information Science

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2543-683X
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Usage Count: A New Indicator to Detect Research Fronts

Guoqiang Liang / Haiyan Hou / Zhigang Hu / Fu Huang / Yajie Wang / Shanshan Zhang
Published Online: 2017-02-18 | DOI: https://doi.org/10.1515/jdis-2017-0005

Abstract

Purpose: Research fronts build on recent work, but using times cited as a traditional indicator to detect research fronts will inevitably result in a certain time lag. This study attempts to explore the effects of usage count as a new indicator to detect research fronts in shortening the time lag of classic indicators in research fronts detection.

Design/methodology/approach: An exploratory study was conducted where the new indicator “usage count” was compared to the traditional citation count, “times cited,” in detecting research fronts of the regenerative medicine domain. An initial topic search of the term “regenerative medicine” returned 10,553 records published between 2000 and 2015 in the Web of Science (WoS). We first ranked these records with usage count and times cited, respectively, and selected the top 2,000 records for each. We then performed a co-citation analysis in order to obtain the citing papers of the co-citation clusters as the research fronts. Finally, we compared the average publication year of the citing papers as well as the mean cited year of the co-citation clusters.

Findings: The citing articles detected by usage count tend to be published more recently compared with times cited within the same research front. Moreover, research fronts detected by usage count tend to be within the last two years, which presents a higher immediacy and real-time feature compared to times cited. There is approximately a three-year time span among the mean cited years (known as “intellectual base”) of all clusters generated by usage count and this figure is about four years in the network of times cited. In comparison to times cited, usage count is a dynamic and instant indicator.

Research limitations: We are trying to find the cutting-edge research fronts, but those generated based on co-citations may refer to the hot research fronts. The usage count of older highly cited papers was not taken into consideration, because the usage count indicator released by WoS only reflects usage logs after February 2013.

Practical implications: The article provides a new perspective on using usage count as a new indicator to detect research fronts.

Originality/value: Usage count can greatly shorten the time lag in research fronts detection, which would be a promising complementary indicator in detection of the latest research fronts.

Keywords: Research front; Citation analysis; Usage count; Times cited

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About the article

Received: 2016-09-26

Revised: 2016-11-27

Accepted: 2016-12-04

Published Online: 2017-02-18

Published in Print: 2017-02-01


Citation Information: Journal of Data and Information Science, ISSN (Online) 2543-683X, DOI: https://doi.org/10.1515/jdis-2017-0005.

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© 2017 Guoqiang Liang et al., published by De Gruyter Open. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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