Analysis of Academic Social Networks in Indonesia
Social network analysis to detect communities in social networks is a complex problem, this is due to differences in community definitions and the complexity of social networks. One of the social networks for researchers is the academic social network (ASN). We define the relationships between nodes...
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| Format: | Article |
| Language: | English |
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Qubahan
2023-12-01
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| Series: | Qubahan Academic Journal |
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| Online Access: | https://journal.qubahan.com/index.php/qaj/article/view/289 |
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| author | Ria Andryani Edi Surya Negara Rezki Syaputra Deni Erlansyah |
| author_facet | Ria Andryani Edi Surya Negara Rezki Syaputra Deni Erlansyah |
| author_sort | Ria Andryani |
| collection | DOAJ |
| description | Social network analysis to detect communities in social networks is a complex problem, this is due to differences in community definitions and the complexity of social networks. One of the social networks for researchers is the academic social network (ASN). We define the relationships between nodes in ASN into two forms, namely interconnection relationships and interaction relationships. Interconnection relationships are researchers' social relationships that are formed from similarities in discipline between researchers, while interaction relationships are researchers' social relationships that are formed through interactions carried out regarding joint article publications. This research aims to measure the social interactions and social interconnections of researchers in Indonesia using the social network analysis method. The ASN data used in this research comes from the academic social network Researchgate. This research produces information on the social networks of scientific groups in Indonesia and a framework for analyzing researchers' social networks using dual identification community mode which has been able to find and understand the structure of the research community based on records of interactions and interconnections with ASN with similarity values in both forms of network connections 85.9%.
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| format | Article |
| id | doaj-art-4994b05eff3147e4b65b60c2f311350c |
| institution | Kabale University |
| issn | 2709-8206 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | Qubahan |
| record_format | Article |
| series | Qubahan Academic Journal |
| spelling | doaj-art-4994b05eff3147e4b65b60c2f311350c2025-02-03T10:12:24ZengQubahanQubahan Academic Journal2709-82062023-12-013410.48161/qaj.v3n4a289289Analysis of Academic Social Networks in IndonesiaRia Andryani0Edi Surya Negara1Rezki Syaputra2Deni Erlansyah3Data Science Interdisciplinary Research Center, Information System, Universitas Bina Darma Palembang, IndonesiaData Science Interdisciplinary Research Center, Information System, Universitas Bina Darma Palembang, IndonesiaData Science Interdisciplinary Research Center, Information System, Universitas Bina Darma Palembang, IndonesiaData Science Interdisciplinary Research Center, Information System, Universitas Bina Darma Palembang, IndonesiaSocial network analysis to detect communities in social networks is a complex problem, this is due to differences in community definitions and the complexity of social networks. One of the social networks for researchers is the academic social network (ASN). We define the relationships between nodes in ASN into two forms, namely interconnection relationships and interaction relationships. Interconnection relationships are researchers' social relationships that are formed from similarities in discipline between researchers, while interaction relationships are researchers' social relationships that are formed through interactions carried out regarding joint article publications. This research aims to measure the social interactions and social interconnections of researchers in Indonesia using the social network analysis method. The ASN data used in this research comes from the academic social network Researchgate. This research produces information on the social networks of scientific groups in Indonesia and a framework for analyzing researchers' social networks using dual identification community mode which has been able to find and understand the structure of the research community based on records of interactions and interconnections with ASN with similarity values in both forms of network connections 85.9%. https://journal.qubahan.com/index.php/qaj/article/view/289Social network analyticsCommunity detectionGraph ClusteringAcademic network |
| spellingShingle | Ria Andryani Edi Surya Negara Rezki Syaputra Deni Erlansyah Analysis of Academic Social Networks in Indonesia Qubahan Academic Journal Social network analytics Community detection Graph Clustering Academic network |
| title | Analysis of Academic Social Networks in Indonesia |
| title_full | Analysis of Academic Social Networks in Indonesia |
| title_fullStr | Analysis of Academic Social Networks in Indonesia |
| title_full_unstemmed | Analysis of Academic Social Networks in Indonesia |
| title_short | Analysis of Academic Social Networks in Indonesia |
| title_sort | analysis of academic social networks in indonesia |
| topic | Social network analytics Community detection Graph Clustering Academic network |
| url | https://journal.qubahan.com/index.php/qaj/article/view/289 |
| work_keys_str_mv | AT riaandryani analysisofacademicsocialnetworksinindonesia AT edisuryanegara analysisofacademicsocialnetworksinindonesia AT rezkisyaputra analysisofacademicsocialnetworksinindonesia AT denierlansyah analysisofacademicsocialnetworksinindonesia |