rosericazondekon/authorvis

A co-authorship network exploration, and link prediction tool of the scientific collaborative research network of Malaria, Tuberculosis and HIV/AIDS in Benin. Roseric Azondekon 2/20/2018 **AuthorVis** is a co-authorship network exploration, and link prediction tool specific to the scientific collaborative research network of Malaria, Tuberculosis and HIV/AIDS in the Republic of Benin. This project is the result of an extensive study of co-authorship network entitled "Network Analysis of Scientific Collaboration and Co-authorship of the Trifecta of Malaria, Tuberculosis and HIV/AIDS in Benin." While many network visualization solutions have already been published, most of them are not specifically adapted to co-authorship network. Even those designed for visualizing co-authorship network have several limitations among others, their inability to satisfactorily display large networks, the lack of interactivity in the display, and the inability for the end user to control the display. This tool not only provides a visualization of each of the networks but allow the end user to query the network. It integrates bibliometrics information to the visualization. In the visualition interface, users can select a particular node or author to emphasize its subnetwork, hover over a node to display author's information or select an edge between two nodes/authors to display information related to materials co-authored by the two nodes defining that particular edge.     Related Work ------------ Various tools for the visualization of co-authorship networks have been proposed: - **NeL2**, a general purpose tool for the visualization of networks as a layered network diagram was proposed by Nakazono, Misue, and Tanaka. - A Java based toolkits was proposed by Liu and colleagues. - The **VVRC**, a Web-based tool was proposed by Barbosa and colleagues. - **VICI**, a Python-based co-authorship tool was proposed by Odoni and colleagues.     Design and Architecture ----------------------- **AuthorVis** is built to a Shiny dashboard with an R based backend system that managed each co-authorship network data as an igraph object. Th …