Tracing scientist's research trends realtimely

被引：43

作者：

Wang, Xianwen ^{[1
,2
]}

Wang, Zhi ^{[1
,2
]}

Xu, Shenmeng ^{[1
,2
]}

机构：

[1] Dalian Univ Technol, Fac Humanities & Social Sci, WISE Lab, Dalian 116085, Peoples R China

[2] Dalian Univ Technol, Sch Publ Adm & Law, Dalian 116085, Peoples R China

来源：

SCIENTOMETRICS | 2013年 / 95卷 / 02期

基金：

高等学校博士学科点专项科研基金;

关键词：

Research trend; Altmetrics; Springer; Realtime; Scientometrics; Download; CITATIONS; DOWNLOADS; NUMBER;

D O I：

10.1007/s11192-012-0884-5

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this research, we propose a method to trace scientist's research trends realtimely. By monitoring the downloads of scientific articles in the journal of Scientometrics for 744 h, namely one month, we investigate the download statistics. Then we aggregate the keywords in these downloaded research papers, and analyze the trends of article downloading and keyword downloading. Furthermore, taking both the downloads of keywords and articles into consideration, we design a method to detect the emerging research trends. We find that in scientometrics field, social media, new indices to quantify scientific productivity (g-index), webometrics, semantic, text mining, and open access are emerging fields that scientometrics researchers are focusing on.

引用

页码：717 / 729

页数：13

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