Ranking Authors in an Academic Network Using Social Network Measures
Online social networks are widely used platforms that enable people to connect with each other. These social media channels provide an active communication platform for people, and they have opened new venues of research for the academic world and business. One of these research areas is measuring t...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-10-01
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| Series: | Applied Sciences |
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| Online Access: | http://www.mdpi.com/2076-3417/8/10/1824 |
| _version_ | 1828841886228414464 |
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| author | Fizza Bibi Hikmat Ullah Khan Tassawar Iqbal Muhammad Farooq Irfan Mehmood Yunyoung Nam |
| author_facet | Fizza Bibi Hikmat Ullah Khan Tassawar Iqbal Muhammad Farooq Irfan Mehmood Yunyoung Nam |
| author_sort | Fizza Bibi |
| collection | DOAJ |
| description | Online social networks are widely used platforms that enable people to connect with each other. These social media channels provide an active communication platform for people, and they have opened new venues of research for the academic world and business. One of these research areas is measuring the influential users in online social networks; and the same is true for academic networks where finding influential authors is an area of interest. In an academic network, citation count, h-index and their variations are used to find top authors. In this article, we propose the adoption of established social network measures, including centrality and prestige, in an academic network to compute the rank of authors. For the empirical analysis, the widely-used dataset of the Digital Bibliography and Library Project (DBLP) is exploited in this research, and the micro-level properties of the network formed in the DBLP co-authorship network are studied. Afterwards, the results are computed using social network measures and evaluated using the standard ranking performance evaluation measures, including Kendall correlation, Overlapping Similarlity (OSim) and Spearman rank-order correlation. The results reveal that the centrality measures are significantly correlated with the citation count and h-index. Consequently, social network measures have potential to be used in an academic network to rank the authors. |
| first_indexed | 2024-12-12T20:13:12Z |
| format | Article |
| id | doaj.art-a1bf963c0c3e4f57afecba78926f39f1 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-12-12T20:13:12Z |
| publishDate | 2018-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-a1bf963c0c3e4f57afecba78926f39f12022-12-22T00:13:28ZengMDPI AGApplied Sciences2076-34172018-10-01810182410.3390/app8101824app8101824Ranking Authors in an Academic Network Using Social Network MeasuresFizza Bibi0Hikmat Ullah Khan1Tassawar Iqbal2Muhammad Farooq3Irfan Mehmood4Yunyoung Nam5Department of Computer Science, COMSATS University Islamabad, Wah Campus, Wah Cant 47040, PakistanDepartment of Computer Science, COMSATS University Islamabad, Wah Campus, Wah Cant 47040, PakistanDepartment of Computer Science, COMSATS University Islamabad, Wah Campus, Wah Cant 47040, PakistanDepartment of Computer Science, COMSATS University Islamabad, Wah Campus, Wah Cant 47040, PakistanDepartment of Software, Sejong University, Seoul 143-747, KoreaDepartment of Computer Science and Engineering, Soonchunhyang University, Asan 31538, KoreaOnline social networks are widely used platforms that enable people to connect with each other. These social media channels provide an active communication platform for people, and they have opened new venues of research for the academic world and business. One of these research areas is measuring the influential users in online social networks; and the same is true for academic networks where finding influential authors is an area of interest. In an academic network, citation count, h-index and their variations are used to find top authors. In this article, we propose the adoption of established social network measures, including centrality and prestige, in an academic network to compute the rank of authors. For the empirical analysis, the widely-used dataset of the Digital Bibliography and Library Project (DBLP) is exploited in this research, and the micro-level properties of the network formed in the DBLP co-authorship network are studied. Afterwards, the results are computed using social network measures and evaluated using the standard ranking performance evaluation measures, including Kendall correlation, Overlapping Similarlity (OSim) and Spearman rank-order correlation. The results reveal that the centrality measures are significantly correlated with the citation count and h-index. Consequently, social network measures have potential to be used in an academic network to rank the authors.http://www.mdpi.com/2076-3417/8/10/1824social network measuresranking authorsacademic indexesco-authorship network |
| spellingShingle | Fizza Bibi Hikmat Ullah Khan Tassawar Iqbal Muhammad Farooq Irfan Mehmood Yunyoung Nam Ranking Authors in an Academic Network Using Social Network Measures Applied Sciences social network measures ranking authors academic indexes co-authorship network |
| title | Ranking Authors in an Academic Network Using Social Network Measures |
| title_full | Ranking Authors in an Academic Network Using Social Network Measures |
| title_fullStr | Ranking Authors in an Academic Network Using Social Network Measures |
| title_full_unstemmed | Ranking Authors in an Academic Network Using Social Network Measures |
| title_short | Ranking Authors in an Academic Network Using Social Network Measures |
| title_sort | ranking authors in an academic network using social network measures |
| topic | social network measures ranking authors academic indexes co-authorship network |
| url | http://www.mdpi.com/2076-3417/8/10/1824 |
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