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

TY - CHAP

T1 - Contextualization of Topics - Browsing through Terms, Authors, Journals and Cluster Allocations

AU - Koopman, Rob

AU - Wang, Shenghui

AU - Scharnhorst, Andrea

N1 - Koopman, R., Wang, S., & Scharnhorst, A. (2015). Contextualization of Topics - Browsing through Terms, Authors, Journals and Cluster Allocations. In A. A. Salah, Y. Tonta, A. A. A. Salah, C. Sugimoto, & U. Al (Eds.), Proceedings of ISSI 2015 Istanbul. 15th International Society of Scientometrics and Informetrics Conference, Istanbul, Turkey, 29th June to 4th July 2015 (pp. 1042–1053). Istanbul: Boğaziçi University Printhouse.

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

M3 - Chapter

SP - 1042

BT - Proceedings of ISSI 2015 Istanbul. 15th International Society of Scientometrics and Informetrics Conference, Istanbul, Turkey, 29th June to 4th July 2015

A2 - Salah, Albert Ali

A2 - Tonta, Yaşar

A2 - Salah, Alkım Almıla Akdağ

A2 - Sugimoto, Cassidy

A2 - Al, Umut

PB - Boğaziçi University

ER -