Contextualization of topics - browsing through terms, authors, journals and cluster allocations
Rob Koopman, Shenghui Wang, Andrea Scharnhorst

TL;DR
This paper demonstrates how the Ariadne visualization tool can be used to explore, compare, and contextualize different clustering solutions within a large bibliographic dataset in astronomy, enhancing understanding of topic delineation.
Contribution
It introduces the application of the Ariadne tool for visual comparison of multiple clustering solutions in a bibliographic dataset, offering a novel approach to topic delineation.
Findings
Ariadne enables visual inspection of cluster similarities.
The tool facilitates browsing through terms, authors, and journals.
It provides a complementary method for comparing clustering algorithms.
Abstract
This paper builds on an innovative Information Retrieval tool, Ariadne. The tool has been developed as an interactive network visualization and browsing tool for large-scale bibliographic databases. It basically allows to gain insights into a topic by contextualizing a search query (Koopman et al., 2015). In this paper, we apply the Ariadne tool to a far smaller dataset of 111,616 documents in astronomy and astrophysics. Labeled as the Berlin dataset, this data have been used by several research teams to apply and later compare different clustering algorithms. The quest for this team effort is how to delineate topics. This paper contributes to this challenge in two different ways. First, we produce one of the different cluster solution and second, we use Ariadne (the method behind it, and the interface - called LittleAriadne) to display cluster solutions of the different group members.…
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Taxonomy
TopicsData Visualization and Analytics · Complex Network Analysis Techniques · Web visibility and informetrics
