Distributed Centrality Analysis of Social Network Data Using MapReduce
dc.authorid | Misra, Sanjay/0000-0002-3556-9331 | |
dc.authorid | BEHERA, RANJAN KUMAR/0000-0001-9267-3621 | |
dc.authorid | Damaševičius, Robertas/0000-0001-9990-1084 | |
dc.authorid | Maskeliunas, Rytis/0000-0002-2809-2213 | |
dc.authorscopusid | 55185224200 | |
dc.authorscopusid | 55428272300 | |
dc.authorscopusid | 56962766700 | |
dc.authorscopusid | 6603451290 | |
dc.authorscopusid | 27467587600 | |
dc.authorwosid | Misra, Sanjay/K-2203-2014 | |
dc.authorwosid | BEHERA, RANJAN KUMAR/I-2680-2017 | |
dc.authorwosid | Rath, Santanu Kumar/O-6685-2017 | |
dc.authorwosid | Damaševičius, Robertas/E-1387-2017 | |
dc.authorwosid | Maskeliunas, Rytis/J-7173-2017 | |
dc.contributor.author | Mısra, Sanjay | |
dc.contributor.author | Rath, Santanu Kumar | |
dc.contributor.author | Misra, Sanjay | |
dc.contributor.author | Damasevicius, Robertas | |
dc.contributor.author | Maskeliunas, Rytis | |
dc.contributor.other | Computer Engineering | |
dc.date.accessioned | 2024-07-05T15:40:01Z | |
dc.date.available | 2024-07-05T15:40:01Z | |
dc.date.issued | 2019 | |
dc.department | Atılım University | en_US |
dc.department-temp | [Behera, Ranjan Kumar; Rath, Santanu Kumar] Natl Inst Technol, Dept Comp Sci & Engn, Rourkela 769008, India; [Misra, Sanjay] Atilim Univ, Dept Comp Engn, TR-06836 Ankara, Turkey; [Misra, Sanjay] Covenant Univ, Dept Elect & Informat Engn, Ota 1023, Nigeria; [Damasevicius, Robertas] Silesian Tech Univ, Fac Appl Math, PL-44100 Gliwice, Poland; [Damasevicius, Robertas; Maskeliunas, Rytis] Kaunas Univ Technol, Dept Multimedia Engn, LT-51368 Kaunas, Lithuania | en_US |
dc.description | Misra, Sanjay/0000-0002-3556-9331; BEHERA, RANJAN KUMAR/0000-0001-9267-3621; Damaševičius, Robertas/0000-0001-9990-1084; Maskeliunas, Rytis/0000-0002-2809-2213 | en_US |
dc.description.abstract | Analyzing the structure of a social network helps in gaining insights into interactions and relationships among users while revealing the patterns of their online behavior. Network centrality is a metric of importance of a network node in a network, which allows revealing the structural patterns and morphology of networks. We propose a distributed computing approach for the calculation of network centrality value for each user using the MapReduce approach in the Hadoop platform, which allows faster and more efficient computation as compared to the conventional implementation. A distributed approach is scalable and helps in efficient computations of large-scale datasets, such as social network data. The proposed approach improves the calculation performance of degree centrality by 39.8%, closeness centrality by 40.7% and eigenvalue centrality by 41.1% using a Twitter dataset. | en_US |
dc.identifier.citation | 18 | |
dc.identifier.doi | 10.3390/a12080161 | |
dc.identifier.issn | 1999-4893 | |
dc.identifier.issue | 8 | en_US |
dc.identifier.scopus | 2-s2.0-85070567051 | |
dc.identifier.scopusquality | Q2 | |
dc.identifier.uri | https://doi.org/10.3390/a12080161 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14411/3285 | |
dc.identifier.volume | 12 | en_US |
dc.identifier.wos | WOS:000482943300028 | |
dc.language.iso | en | en_US |
dc.publisher | Mdpi | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | distributed computing | en_US |
dc.subject | social network analysis | en_US |
dc.subject | network centrality | en_US |
dc.subject | network pattern recognition | en_US |
dc.subject | MapReduce | en_US |
dc.title | Distributed Centrality Analysis of Social Network Data Using MapReduce | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication | |
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