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 us...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.展开更多
Open-access(OA)Papers'impact research has become more and more popular in scientific evaluation,and it is also an important issue that scientific research management departments have been discussing.Since previous...Open-access(OA)Papers'impact research has become more and more popular in scientific evaluation,and it is also an important issue that scientific research management departments have been discussing.Since previous studies have focused on the influence of traditional literature indicators research papers,this study combines traditional literature indicators and Altmetrics indexes.This article uses the data of Chinese social science open-access(OA)papers in WoS for the past 5 years as a sample and uses descriptive statistics,correlation analysis,and regression analysis to explore the impact of traditional paper indicators and Altmetrics indexes on the use of papers.The results show that both literature indexes and social media indexes have a significant impact on the use of papers,and deepen the understanding of the impact factor of research papers.Overall,the results of this study prove that traditional literature indexes and social media indexes have an impact on the use of papers.This method promotes the role of social media indexes in the influence of paper use.Finally,the reasons for the influence factors of the paper are analyzed,and relevant suggestions are put forward.展开更多
基金supported by the National Social Science Foundation of China(Grant No.:14BTQ030)
文摘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.
文摘Open-access(OA)Papers'impact research has become more and more popular in scientific evaluation,and it is also an important issue that scientific research management departments have been discussing.Since previous studies have focused on the influence of traditional literature indicators research papers,this study combines traditional literature indicators and Altmetrics indexes.This article uses the data of Chinese social science open-access(OA)papers in WoS for the past 5 years as a sample and uses descriptive statistics,correlation analysis,and regression analysis to explore the impact of traditional paper indicators and Altmetrics indexes on the use of papers.The results show that both literature indexes and social media indexes have a significant impact on the use of papers,and deepen the understanding of the impact factor of research papers.Overall,the results of this study prove that traditional literature indexes and social media indexes have an impact on the use of papers.This method promotes the role of social media indexes in the influence of paper use.Finally,the reasons for the influence factors of the paper are analyzed,and relevant suggestions are put forward.
