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We have collected and analyzed all relevant publications on Big Data, as indexed in Scopus, through a quantitative as well as textual characterization. The analysis attempts to dwell into parameters like research productivity, growth of research and citations, thematic trends, top publication sources and emerging topics in this field. The analytical study also investigates country-wise publications output and impact in terms of average citations per paper, country-level collaboration patterns, authorship and leading contributors (countries, institutions) etc. The scholarly publication data is also subjected to a detailed textual analysis method to identify key themes in Big Data research, disciplinary variations and thematic trends and patterns. The results produce interesting inferences. Quantitative measures show that there has been a tremendous increase in number of publications related to Big Data during last few years. Research work in Big Data, though primarily considered a sub-discipline of Computer Science, is now carried out by researchers in many disciplines. Thematic analysis of publications in Big Data show that it\u2019s a discipline involving research interest from fields as diverse as Medicine to Social Sciences. The paper also identifies major keywords now associated with Big Data research such as Cloud Computing, Deep Learning, Social Media and Data Analytics. This helps in a thorough understanding and visualization of the Big Data research area.<\/jats:p>","DOI":"10.3233\/jifs-179016","type":"journal-article","created":{"date-parts":[[2019,3,26]],"date-time":"2019-03-26T18:56:22Z","timestamp":1553626582000},"page":"4659-4675","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":11,"title":["A quantitative and text-based characterization of big data research"],"prefix":"10.1177","volume":"36","author":[{"given":"Vedika","family":"Gupta","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, National Institute of Technology Delhi, Delhi, India"}]},{"given":"Vivek Kumar","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Banaras Hindu University, Varanasi, India"}]},{"given":"Udayan","family":"Ghose","sequence":"additional","affiliation":[{"name":"University School of Information and Communication Technology, Guru Gobind Singh Indraprastha University, Dwarka, Delhi, India"}]},{"given":"Pankaj","family":"Mukhija","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronics Engineering, National Institute of Technology Delhi, Delhi, India"}]}],"member":"179","published-online":{"date-parts":[[2019,3,23]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2014.2332453"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1089\/big.2013.1508"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2016.2641460"},{"key":"e_1_3_2_5_2","unstructured":"M.A.Beyer and D.Laney The importance of \u201cbig data\u201d: A definition Stamford CT: Gartner (2012) 2014\u20132018."},{"key":"e_1_3_2_6_2","first-page":"1","article-title":"Extracting value from chaos","volume":"1142","author":"Gantz J.","year":"2011","unstructured":"J.Gantz and D.Reinsel, Extracting value from chaos, IDC Iview1142 (2011), 1\u201312.","journal-title":"IDC Iview"},{"key":"e_1_3_2_7_2","article-title":"Analytics: The real-world use of big data: How innovative enterprises extract value from uncertain data, Executive Report","author":"Schroeck M.","year":"2012","unstructured":"M.Schroeck, R.Shockley, J.Smart, D.Romero-Morales and P.Tufano, Analytics: The real-world use of big data: How innovative enterprises extract value from uncertain data, Executive Report, IBM Institute for Business Value and Said Business School at the University of Oxford, 2012.","journal-title":"IBM Institute for Business Value and Said Business School at the University of Oxford"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bdr.2017.02.002"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-015-0023-2"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bdr.2014.07.005"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bdr.2016.05.002"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1089\/big.2015.0043"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1089\/big.2016.29011.vdc"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bdr.2015.02.006"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1089\/big.2014.0061"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1089\/big.2014.0064"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bdr.2015.01.005"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bdr.2015.01.006"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-014-0008-6"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1080\/1369118X.2012.678878"},{"key":"e_1_3_2_21_2","doi-asserted-by":"crossref","unstructured":"M.Hoskins Big data 2.0: Cataclysm or catalyst? 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