On The Co-authorship Network Of Big Data Research Field

According to the testing and studying, Harvard University psychologist David Land and his colleagues found "The first instinct of human is cooperation". In recent years,scientific cooperation has becoming an important form of scientific research, moreover the scope and scale of scientific cooperation have increased rapidly. In an age of big data, and when many countries have adopted development policies in big data field, so what about scientific cooperation in big data research field? Under this background, this dissertation mainly focus on journal article in big data field from 2003 to 2015, and then explore co-authorship phenomenon and analysis co-authorship rules of development as well as co-authorship network internal structure by using a combination of social network analysis methods and complex networks theory.Firstly, from the perspective of statistic analysis, the paper as 1877 articles and 2263 Proceedings paper in "Web of Science Core Collection" a sample, which statistics and analysis these two literature output speed.The results have shown that only article is increasing at theexponential speed.Then explore the core countries, institutions, and the author in big data research field. Secondly, we drew the co-authorship network of literature in big data research field by scientometric analysis software. A series of networks showed macrostructure of co-authorship network and microstructure which are formations of core nodes. In level of the whole network, we explored network integral structure features, such as, degree distribution of co-authorship network, cluster coefficient, networks density. In level of the micro network, we explored distribution of cooperation resources of Excellent scientific institutions through k-core decomposition.we explored the small-world characteristics of Cohesive Subgroups and revealed the co-authorship rule of big data research field by virtue of Cohesive Subgroups Analysis.Eventually, according to a comprehensive set ofindicators, such as, the degree centrality,betweenness centrality, H index,etc. Academicinstitutions and researchers were compared for theiracademic influence. Then we explored who are the core academicinstitutions and core researchers. The results showed that the influence of the two bodies is mainly dependent diffusion ability of knowledge and the extent of its own resources.To sum up, a series of scientometric analysis and knowledge graph show that the development of co-authorship in big data research field is good, the scale and breadth of cooperation have some achievements, but there are a lot of room to grow. The research and development capabilities of data handling techniques of our country which occupy a more influential position in the international environment, but on the paper quality and the good partner resources remains to be further improved.