Modeling And Analyzing The Coevolution Between Scientific Collaborations And Citations

Academic ideas can be propagated in two ways.One is the direct way,that is,researchers communicate with each other and collaborate to produce new ideas,which is showed as the coauthorship;the other is the indirect way,namely,researchers read others’ papers and study their ideas and technology,which is characterized by the citation of papers.Therefore,it’s helpful for the deep understanding of the collaboration behavior and citation behavior themselves and beneficial for the exploring of the propagation law of academic ideas to research scientific collaborations and citations.In the view of scientometrics,both scientific collaboration behavior and citation network have great research significance.In scientific collaboration networks,nodes represent authors and edges represent the cooperation relationships between those authors.While citation networks are directed networks,where papers are regarded as nodes and the citation relationships as edges.Both the research interests of authors and the topic of academic papers can be expressed by the geometric way.So we use geometry and statistical knowledge,and the main work is as follows:(1)A “fat tail”,which can be approximately fitted by a power law,is discovered in the distribution of the number of papers per author.To reveal the mechanism of the “fat tail”,a geometric hypergraph model is proposed with the consideration of author’s academic influence,research interesting,and replacement of members,etc.,in which authors are regarded as nodes,the coauthorships of authors in papers are treated as hyperedges and the number of papers per author is represented by hyperdegree.The model deduces the emergence process of the “fat tail” and gives a reasonable social explanation.The analysis and simulation results show that the collaborative modes of various disciplines can be well expressed by the model,which reveals the similarities and specialities of scientific collaboration behaviors in different research fields.(2)For researchers,do activity in academic society influence their careers? In scientometrics,the activity can be expressed through the number of collaborators and scientific careers through the number of publications and citations of authors.We provide empirical evidence from four datasets of representative journals and explore the correlations between each two of the three indexes.By using a hypothetical extraction method,we divide authors into patterns reflecting the different extent of preference to social activity,according to their contributions to the correlation between the number of collaborators and that of papers.Furthermore,we compare the expected value as well as the distribution of publications and citations for sociable authors and that of others.The correlation coefficient,the mean value and the distribution of publications and citations are considered together,then we draw a conclusion that social activity could be favourable for authors to promote academic outcomes and obtain recognition.(3)Collaborations and citations within scientific research grow simultaneously and interact dynamically.Modelling the coevolution between them helps to study many phenomena that can be approached only through combining citation and coauthorship data.A geometric graph for the coevolution is proposed,the mechanism of which synthetically expresses the interactive impacts of authors and papers in a geometrical way.The validation shows the ability to reproduce a range of features observed with citation and coauthorship data combined and separately.Particularly,in the empirical distribution of citations per author there exist two limits,in which the distribution appears as a generalized Poisson and a power-law respectively.Our model successfully reproduces the shape of the distribution,and provides an explanation for how the shape emerges via the decisions of authors.The model also captures the empirically positive correlations between the numbers of authors’ papers,citations and collaborators.