{"_buckets": {"deposit": "0c16cbf4-539f-40bb-b5b9-d07d449d30b5"}, "_deposit": {"id": "4605", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4605"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4605", "sets": ["1597824273898", "user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Community Detection in Scientific Co-Authorship Networks using Neo4j", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "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."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "co-authorship network"}, {"interim": "community detection"}, {"interim": "modularity"}, {"interim": "Neo4j"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2020-03-17"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Community Detection in Scientific Co-Authorship Networks using Neo4j.pdf", "filesize": [{"value": "403 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 403000.0, "url": {"url": "https://meral.edu.mm/record/4605/files/Community Detection in Scientific Co-Authorship Networks using Neo4j.pdf"}, "version_id": "bb142767-188b-42b7-8182-11fdc56a5094"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Proceedings of the Eighteenth International Conference On Computer Applications (ICCA 2020)", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "", "subitem_c_date": "", "subitem_conference_title": "", "subitem_part": "", "subitem_place": "", "subitem_session": "", "subitem_website": ""}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{"subitem_book_title": "", "subitem_isbn": "", "subitem_pages": "", "subitem_place": "", "subitem_publisher": ""}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Aung, Thet Thet"}, {"subitem_authors_fullname": "Nyunt, Thi Thi Soe"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2020-02-28"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "978-1-7281-5925-6"}, "item_title": "Community Detection in Scientific Co-Authorship Networks using Neo4j", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004605", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-03-17"}, "publish_date": "2020-03-17", "publish_status": "0", "recid": "4605", "relation": {}, "relation_version_is_last": true, "title": ["Community Detection in Scientific Co-Authorship Networks using Neo4j"], "weko_shared_id": -1}