Analysis on cited times of papers published in Neural Regeneration Research

Introduction Publication Name=Neural Regeneration Research （NRR） Timespan=2008-2011. Databases=SCI-EXPANDED, SSCI, A＆HCI, CPCI-S, CPCI-SSH. Web of Science Categories： CELL BIOLOGY （938）, NEUROSCIENCE （938） Document Types： ARTICLE （922）, REVIEW （13）, EDITORIAL MATERIAL （2）, LETTER （1） Search time： 23/06/2011 A total of 938 articles published till the search time in NRR are searched, including 315 papers published in 2008, 185 in 2009, 321 in 2010, and 117 in 2011. Totally 111 papers have been cited and the total number of citations is 171. There are 76 self-citations, and 95 non-self citations, which are scattered in 85 journals. The citation situations are listed as follows.

Influences of digital resource acquisition on scientific research behaviors——The statistical analysis on the full-text downloading quantity and cited times

With the emergence and further development of the digital library, the approaches of information acquisition correspondingly change a lot. This paper makes a statistical analysis on the journal downloading and citation behaviors under the digital environment conceived by the National Science Library(NSL), Chinese Academy of Sciences(CAS). It can be seen that the development of digital resources has influenced scientific research behaviors. For example, the large quantity of full-text downloading will maintain; the trend of journal downloading behaviors is basically same as the journal citation behavior; journals with large quantity of full-text downloading also boast the high cited times, and vice versa. Furthermore, authors make a linear regression analysis, with the journal downloading amount as the independent variable and journal cited times as dependent variable. Then they also prove the positive correlation between the journal downloading and citation behaviors by means of Pearson's correlation coefficient formula.

Paper Analysis of Shanghai Ocean University in Bibliometric Method from Web of Science

The data of this research was mainly collected from the Web of Science (WOS) and Incites database platform, which was filtered and cataloged according to the different platforms. For tracing the change in scientific research at Shanghai Ocean University, make use of Bibliometric analysis to get the image and table of highly cited papers and hot papers. In this study, the scientific aspects in highly cited papers and hot papers, published in the last year in the core collection of Web of Science, were taken as objects, and office software was used as the main tool to carry out bibliometric and figure analysis. From the four aspects to find the difference in these fields, the production of specific fields and cited times is inconsistent. And suggest the department and management adjust the policy and method via elastic personnel and rewards to prompt the advancement of the research fields.

Usage Count： A New Indicator to Detect Research Fronts

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.

Impact factor research of open -access (OA) papers in Chinese social sciences

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.