↓ Skip to main content

PLOS

Identifying Overlapping and Hierarchical Thematic Structures in Networks of Scholarly Papers: A Comparison of Three Approaches

Overview of attention for article published in PLOS ONE, March 2012
Altmetric Badge

Mentioned by

blogs
1 blog
twitter
3 X users

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
55 Mendeley
citeulike
2 CiteULike
Title
Identifying Overlapping and Hierarchical Thematic Structures in Networks of Scholarly Papers: A Comparison of Three Approaches
Published in
PLOS ONE, March 2012
DOI 10.1371/journal.pone.0033255
Pubmed ID
Authors

Frank Havemann, Jochen Gläser, Michael Heinz, Alexander Struck

Abstract

The aim of this paper is to introduce and assess three algorithms for the identification of overlapping thematic structures in networks of papers. We implemented three recently proposed approaches to the identification of overlapping and hierarchical substructures in graphs and applied the corresponding algorithms to a network of 492 information-science papers coupled via their cited sources. The thematic substructures obtained and overlaps produced by the three hierarchical cluster algorithms were compared to a content-based categorisation, which we based on the interpretation of titles, abstracts, and keywords. We defined sets of papers dealing with three topics located on different levels of aggregation: h-index, webometrics, and bibliometrics. We identified these topics with branches in the dendrograms produced by the three cluster algorithms and compared the overlapping topics they detected with one another and with the three predefined paper sets. We discuss the advantages and drawbacks of applying the three approaches to paper networks in research fields.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Australia 1 2%
India 1 2%
United Kingdom 1 2%
Canada 1 2%
Denmark 1 2%
China 1 2%
Spain 1 2%
United States 1 2%
Other 0 0%
Unknown 46 84%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 24%
Librarian 6 11%
Researcher 5 9%
Student > Master 5 9%
Student > Postgraduate 4 7%
Other 13 24%
Unknown 9 16%
Readers by discipline Count As %
Computer Science 24 44%
Social Sciences 7 13%
Business, Management and Accounting 4 7%
Medicine and Dentistry 4 7%
Physics and Astronomy 2 4%
Other 4 7%
Unknown 10 18%