Research Of Information Relationship Of Complex Interface Based On Information Nodes

Big data and information visualization emerge with the rapid development of information age. How to extract meaningful information from mass data and convey the data information to users through an intuitive, beautiful and easy-to- manipulate way has become the research focus of information visualization. This paper does a thorough research about complex network and information visualization via both qualitative and quantitative research, and visualizes and analyzes a complex network with the combination of interaction design and emotion design.Co-authorship network is the cooperation network between authors researching in the same academic field. It features large amounts of nodes and complex network. This essay focuses on the research of co-authorship network, extracts co-authorship information of "Social Network" from 2010 to 2015 by NoteExpress, then integrates the information into certain format that can be read and used by Pajek, Gephi and Tableau, visualizing the co-authorship network and calculate certain parameters. In this essay, following work is done:(1) Research in the history and current situation of complex network and application scenarios of knowledge graph, focusing on the research filed of complex network and the parameters for determinating the importance of nodes;(2) Integrate the concept of interaction design and emotion design into the interface design of information visualization. Point out that good information interface design should meet five factors of user experience, and visibility, aesthetics, emotional experience, readability, progressing step by step and narrativity of information.(3) Research main patterns and implementation methods of information visualization. Calculate the parameters of the importance of nodes and visualize the information of co-authorship network with Pajek, Gephi and Tableau as the visualization tools.Through the research, this paper explored the visualization methods of co-authorship network and built appropriate visualization patterns for authors network, keywords network, number of papers and number of occurs in the co-authorship information.