Network Graph Visualization

The visualization was built using data from over 110,000 articles published between 2009 and 2018, found in 191 academic journals from the Web of Science database. We analyzed the bibliographic record (title, keywords, author, cited references, and abstract) for each article and created a bibliographic coupling network, to link articles sharing at least two common references.

Next, we used an algorithm to detect groups of articles with densely shared links. Articles belonging to the same group are gathered into nodes, or circles, which we call “topics.” The circle size is proportional to the number of articles it contains. The thickness of the lines between topics indicates how strongly they are connected. Then, we applied the same algorithm to the articles in each topic to split them into subtopics.

After the map was built, we reviewed the most cited and representative papers in each topic and subtopic to create labels and descriptions. The data analysis and visualization was completed using BiblioTools and D3.