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  1. University of Computer Studies, Yangon
  2. Conferences

Community Detection in Scientific Co-Authorship Networks using Neo4j

http://hdl.handle.net/20.500.12678/0000004605
http://hdl.handle.net/20.500.12678/0000004605
52e418b5-84ad-40ef-89bc-73c3556ffdb9
0c16cbf4-539f-40bb-b5b9-d07d449d30b5
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Community Community Detection in Scientific Co-Authorship Networks using Neo4j.pdf (403 Kb)
Publication type
Article
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Publication
Title
Title Community Detection in Scientific Co-Authorship Networks using Neo4j
Language en
Publication date 2020-02-28
Authors
Aung, Thet Thet
Nyunt, Thi Thi Soe
Description
Community structure in scientific collaborationnetwork has become an important research area. Coauthor of a paper can be thought of as a collaborativedocument between more than one authors. Communitydetection in co-authorship network reveals characteristicpatterns of scientific collaboration in computer scienceresearch and help to understand the identity-organizationof the author community. Louvain algorithm is a simple,easy to implement and efficient to recognize community inhuge networks. In this paper, it is used to examine thestructure of community in Computer University’s coauthornetwork in Myanmar. Neo4j is also used to visualize the coauthorship network analysis results. Modularity is used tomeasure the quality of the cluster structure found bycommunity discovery algorithms. In experiment, Louvainalgorithm gives more effective qualitative communitystructures than other algorithms in co-authorship network.
Keywords
co-authorship network, community detection, modularity, Neo4j
Identifier 978-1-7281-5925-6
Journal articles
Proceedings of the Eighteenth International Conference On Computer Applications (ICCA 2020)
Conference papers
Books/reports/chapters
Thesis/dissertations
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