Contextualization of Topics - Browsing through Terms, Authors, Journals and Cluster Allocations

Rob Koopman, Shenghui Wang, Andrea Scharnhorst

Research output: Chapter in book/volumeChapterScientificpeer-review

62 Downloads (Pure)


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 solutions and second, we use Ariadne (the method behind it, and the interface - called LittleAriadne) to display cluster solutions of the different group members. By providing a tool that allows the visual inspection of the similarity of article clusters produced by different algorithms, we present a complementary approach to other possible means of comparison. More particularly, we discuss how we can - with LittleAriadne - browse through the network of topical terms, authors, journals and cluster solutions in the Berlin dataset and compare cluster solutions as well as see their context.
Original languageEnglish
Title of host publicationProceedings of ISSI 2015 Istanbul. 15th International Society of Scientometrics and Informetrics Conference, Istanbul, Turkey, 29th June to 4th July 2015
EditorsAlbert Ali Salah, Yaşar Tonta, Alkım Almıla Akdağ Salah, Cassidy Sugimoto, Umut Al
PublisherBoğaziçi University
Number of pages1053
Publication statusPublished - 2015


Dive into the research topics of 'Contextualization of Topics - Browsing through Terms, Authors, Journals and Cluster Allocations'. Together they form a unique fingerprint.

Cite this