Decomposing social and semantic networks in emerging "big data" research

被引:68
作者
Park, Han Woo [1 ]
Leydesdorff, Loet [2 ]
机构
[1] YeungNam Univ, Dept Media & Commun, Gyongsan 712749, Gyeongsangbuk D, South Korea
[2] Univ Amsterdam, Amsterdam Sch Commun Res ASCoR, NL-1012 CX Amsterdam, Netherlands
基金
新加坡国家研究基金会;
关键词
Data science; Big data; International co-authorship; Social network analysis; SCI; Semantic network; CENTRALITY; SCIENCE;
D O I
10.1016/j.joi.2013.05.004
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper examines the structural patterns of networks of internationally co-authored SCI papers in the domain of research driven by big data and provides an empirical analysis of semantic patterns of paper titles. The results based on data collected from the DVD version of the 2011 SCI database identify the U.S. as the most central country, followed by the U.K., Germany, France, Italy, Australia, the Netherlands, Canada, and Spain, in that order. However, some countries (e.g., Portugal) with low degree centrality occupied relatively central positions in terms of betweenness centrality. The results of the semantic network analysis suggest that internationally co-authored papers tend to focus on primary technologies, particularly in terms of programming and related database issues. The results show that a combination of words and locations can provide a richer representation of an emerging field of science than the sum of the two separate representations. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:756 / 765
页数:10
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