Research networks in the field of forced migration and refugee studies in Germany

Instruction Booklet

Instruction Booklet: Network Analysis (Shiny App) 

Our app allows you to explore a network of institutions related to Forced Migration and Refugee Studies and their connections. You can filter and visualize the network based on different criteria, search for specific institutions, and download the generated graph.

Getting Started 

Interface: The app consists of three horizontal sections. The top section contains the main controls, the middle section displays the network graph and the sidebar, and the bottom one shows additional information. 

Main Controls
  • Filters: In the upper section, you will find several filter options to refine the displayed network. Use these filters to customize the network based on your preferences. These filters include: 

    • Institution type - University, State Institution, Non-University, Foundation, University of Applied Sciences, Other. 

    • Field of research - Development, Governance, Human Rights, Migration, Peace and Conflict. 

    • Class of institution - research, finance, research & finance, other. 

    • Start and End Year - period of the network.

  • Search: To search for specific institutions, use the search box located in the top row. Enter the abbreviation of the institution you are looking for, and the app will highlight it in the network graph with its connections.

  • Display Options: You can choose to display unconnected nodes by toggling the "Display unconnected nodes" checkbox. This option shows or hides nodes that with the current filters are not connected to any other institution in the network.

  • Graph: The network graph is displayed in the middle row using the VisNetwork visualization. You can explore the graph by zooming in and out, dragging to move around, and hovering over nodes for additional information. The graph displays institutions as nodes, and the connections between them as edges. The size and color of the nodes represent different attributes of the institutions. 

  • Sidebar: On the left side of the middle section, you will find a sidebar. Click the "⇅" button to toggle the sidebar. The sidebar provides information about the iconography and the colors used in the graph.

  • Hover tag.  When the mouse is over a specific node It displays information on three aspects: 

    • Total Projects: This refers to the total number of unique projects associated with the institution, regardless of the current filter selection. It represents the overall project count. 

    • Current Connected Projects: This indicates the current sum of projects in which the institution collaborates with other institutions. It is important to note that this sum includes all project connections, and some projects might be included twice. Consequently, the count may be higher than the total projects figure, which suggests that multiple institutions work on the same project. 

    • Current Partner Institutions: This represents the current number of partner institutions with whom the institution is actively collaborating. Unlike the previous aspect, this count is independent of the number of projects. It focuses solely on the institutions the current filter selection identifies as partners, providing insights into the institution's collaborative network. 

  • Number of Nodes: On the left side, you will see the number of active institutions currently displayed in the graph. This count updates dynamically based on the applied filters. 

  • Hover tag.  It displays information on three aspects:

    • Total Projects: This refers to the total number of unique projects associated with the institution, regardless of the current filter selection. It represents the overall project count. 

    • Current Connected Projects: This indicates the current sum of projects in which the institution collaborates with other institutions. It is important to note that this sum includes all project connections, and some projects might be included twice. Consequently, the count may be higher than the total projects figure, which suggests that multiple institutions work on the same project. 

    • Current Partner Institutions: This represents the current number of partner institutions with whom the institution is actively collaborating. Unlike the previous aspect, this count is independent of the number of projects. It focuses solely on the institutions the current filter selection identifies as partners, providing insights into the institution's collaborative network.

  • Number of projects. In each edge between two nodes of the graph, you will find a number that pictures the quantity of projects that connect both institutions. 

Additional Information

The bottom row of the app contains two controls: 

  • Number of Nodes: On the left side, you will see the number of active institutions currently displayed in the graph. This count updates dynamically based on the applied filters. 

  • Download Graph: On the right side, you can download the generated graph as a file. Click the "Download graph" button to save the graph for further analysis or sharing 

Clarification 

To generate acronyms for institutions, an automated process is employed in some cases. The process involves combining the capital letters of the holding institution name, followed by a hyphen (-), and then the capital letters of the institution's name. 

About

This application was made in R language and environment for statistical computing. Particularly, it relies Shiny App and VisNetwork packages (see citation below).  

Almende B.V. and Contributors, Thieurmel B (2022). visNetwork: Network Visualization using 'vis.js' Library . R package 
  version 2.1.2, < https://CRAN.R-project.org/package=visNetwork >. 

  • Chang W, Cheng J, Allaire J, Sievert C, Schloerke B, Xie Y, Allen J, McPherson J, Dipert A, Borges B (2023). shiny: Web Application Framework for R. R package version 1.7.4.1, <https://CRAN.R-project.org/package=shiny

  • R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.