{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T10:06:00Z","timestamp":1760609160731,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2019,8,9]],"date-time":"2019-08-09T00:00:00Z","timestamp":1565308800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/a12080161","type":"journal-article","created":{"date-parts":[[2019,8,9]],"date-time":"2019-08-09T11:11:31Z","timestamp":1565349091000},"page":"161","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Distributed Centrality Analysis of Social Network Data Using MapReduce"],"prefix":"10.3390","volume":"12","author":[{"given":"Ranjan","family":"Kumar Behera","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, National Institute of Technology, Rourkela 769008, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Santanu","family":"Kumar Rath","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, National Institute of Technology, Rourkela 769008, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3556-9331","authenticated-orcid":false,"given":"Sanjay","family":"Misra","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Atilim University, Incek, Ankara 06836, Turkey"},{"name":"Department of Electrical and Information Engineering, Covenant University, Ota 1023, Nigeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9990-1084","authenticated-orcid":false,"given":"Robertas","family":"Dama\u0161evi\u010dius","sequence":"additional","affiliation":[{"name":"Faculty of Applied Mathematics, Silesian University of Technology, 44-100 Gliwice, Poland"},{"name":"Department of Multimedia Engineering, Kaunas University of Technology, 51368 Kaunas, Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2809-2213","authenticated-orcid":false,"given":"Rytis","family":"Maskeli\u016bnas","sequence":"additional","affiliation":[{"name":"Department of Multimedia Engineering, Kaunas University of Technology, 51368 Kaunas, Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,8,9]]},"reference":[{"key":"ref_1","first-page":"367","article-title":"A critical review of centrality measures in social networks","volume":"52","author":"Landher","year":"2010","journal-title":"Wirtschaftsinformatik"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"El Gamal, A., and Kim, Y.H. 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