Talent is a kind of very crucial economic resource and a source of creative power in science, technology, business, arts and culture and other activities. The international mobility of talents plays a very important role in not only driving scientific progress, but also impacting on the development of economy and society, at the level of original and destination countries, even all over the world.

This paper investigates international talent mobility with two kinds of big data diagnostic tools----complex network theory and system identification theory， and also proposes a systematic and quantitative analyzing approach for sociological problems. The study and the analyzing approach are quantitative, so that the results in this paper are more credible than other empirical results.

In this paper, the international talent mobility is modelled as complex network by setting nodes of the network as countries, and viewing edge weights as talent attraction index for destination countries and talent retentiveness index for original countries, which are also unknown parameters to be identified. Next, the relationship between them is discussed. Also, the unknown parameters and topology of the networked model are obtained by system identification. With the help of complex network analysis, the characters of the international talent mobility are obtained.

According to the proposed networked model, it is known that international talent mobility is not balanced.The result of this paper may support further researches on predicting talent mobility trend and political suggestions for cultivating, attracting and retaining talents in the world. The future work should also include the analysis on the factors and influences of international talent mobility based on the obtained networked model by explicating linear regression or other methods according to statistics in quantification.