Usage Count: A New Indicator to Detect Research Fronts

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. F indings:T he 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.

A review of the use and utility of industrial network-based open source simulators: functionality, security, and policy viewpoints

“…Two key metric indicators for research fronts include “Usage Count” and “Times Cited,” with specific application to the WoS database of articles. 31 “Times Cited” seems to be the more common metric of the two adopted for analyzing citation fronts, despite its limitations of characterizing elongated time-lags in demonstrating the effects of research fronts and an inability to reflect current interests of the research community. With the case for using “Usage Count” as a viable alternative or complement still open in the research community, the “Times Cited” indicator is adopted in this study as the criterion for evaluating the top 10 articles from the keyword search results on the WoS database for each of the selected simulators.…”

“…Two key metric indicators for research fronts include ''Usage Count'' and ''Times Cited,'' with specific application to the WoS database of articles. 31 ''Times Cited'' seems to be the more common metric of the two adopted for analyzing citation fronts, despite its limitations of characterizing elongated time-lags in demonstrating the effects of research fronts and an inability to reflect current interests of the research community.…”

“…To assess how widely the selected simulators are used, and to understand the kind of research built around them and their applications, a systematic literature review 30 of related works was done spanning the period of 2010-2018 to obtain key research results that focus on individual simulator workspaces. This is termed ''research fronts,'' 31 referring to clusters of papers that share a common intellectual base. In this study, the common intellectual base refers to peer-reviewed research and knowledgeable outputs related to selected simulation tools.…”

Horizon Scanning in Tissue Engineering Using Citation Network Analysis

“…However, most studies aimed at using bibliometric analyses for horizon scanning have focused on setting models and indicators of the analytical procedure, whereas limited studies have focused on the differences in developmental history, publication trends, and citation trends in each research field [ 17 – 21 ].…”

Can usage be used for scholars’ evaluation in the construction of smart libraries?

“…Lieu and Zhao (2019) and Zhao et al (2018) studied the relationship among database payment, fund funding and user usage data. Liang et al (2017) conducted a comparative study between traditional citation data and Usage data based on WoS database in fields of regenerative medicine and discovered that Usage is a comparatively dynamic and real-time index compared with lagged traditional citation data. Besides, Chi and Glanzel (2018) did a more in-depth study and proposed a new journal metricthe Journals Usage Index, which is proposed to supplement journal impact measures.…”