Google Scholar is a search engine used to look up scholarly literature such as journal articles, white papers, theses and books across various disciplines. It allows researchers to see the number of citations for a specific publication as well as a list of related articles. That being said, Google Scholar does not include the number or list of references used in the publication with users having to directly visit the online database where the paper is stored to view this information. Both aspects of the number of citations and number of references are important measures for determining the quality of a paper.
In addition to searching for papers, Google Scholar allows authors to create public profiles and monitor the number of citations to their publications. Author public profiles display a list of papers published by the author along with the number of citations for each paper and the year in which it was published while an aggregated figure of number of citations for each year is shown in a bar graph.
While researchers are interested in number of citations and number of references of a paper, authors have an interest in the number of citations, topic fields in which their paper is cited and from which institution citing authors originate from.
With this in mind, it was thought that a visualisation of the networks between Google Scholar citations (cited by) and references (cited) organised by geographic location and discipline be created for use by both academics and Google Scholar users. This would be done for a single paper of the author.
A visualisation such as this would allow:
Data for this visualisation will be gathered from the following sources:
Before the final design was implemented, research was done into existing citation visualisations. These were found to be in a static and interactive form. Static visualisations included images which simply display the data and interactive visualisations involved interfaces which allow the data to be further explored.
Read MoreOnce the final design was implemented, we evaluated the strengths and weaknesses of our visualisation based on whether we were able to accurately visualise the given data; effectively convey the dimensions of the given data (cited by, cited, earlier/recent, category) and the degree of usability of the interface. Read More
A break down of the division of work between team members listing their contributions to the project.
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