{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T20:44:15Z","timestamp":1779223455323,"version":"3.51.4"},"reference-count":90,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2020,1,28]],"date-time":"2020-01-28T00:00:00Z","timestamp":1580169600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Research, Technology, and Higher Education","award":["NKB-1844\/UN2.R3.1\/HKP.05.00\/2019."],"award-info":[{"award-number":["NKB-1844\/UN2.R3.1\/HKP.05.00\/2019."]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Recently, the popularity of big data as a research field has shown continuous and wide-scale growth. This study aims to capture the scientific structure and topic evolution of big data research using bibliometrics and text mining-based analysis methods. Bibliographic data of journal articles regarding big data published between 2009 to 2018 were collected from the Scopus database and analyzed. The results show a significant growth of publications since 2014. Furthermore, the findings of this study highlight the core journals, most cited articles, top productive authors, countries, and institutions. Secondly, a unique approach to identifying and analyzing major research themes in big data publications was proposed. Keywords were clustered, and each cluster was labeled as a theme. Moreover, the papers were divided into four sub-periods to observe the thematic evolution. The theme mapping reveals that research on big data is dominated by big data analytics, which covers methods, tools, supporting infrastructure, and applications. Other critical aspects of big data research are security and privacy. Social networks and the Internet of things are significant sources of big data, and the resources and services offered by cloud computing strongly support the management and processing of big data.<\/jats:p>","DOI":"10.3390\/info11020069","type":"journal-article","created":{"date-parts":[[2020,1,29]],"date-time":"2020-01-29T10:51:07Z","timestamp":1580295067000},"page":"69","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":68,"title":["Theme Mapping and Bibliometrics Analysis of One Decade of Big Data Research in the Scopus Database"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9460-6895","authenticated-orcid":false,"given":"Anne","family":"Parlina","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Universitas Indonesia, Depok, Jawa Barat 16424, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0374-4465","authenticated-orcid":false,"given":"Kalamullah","family":"Ramli","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Universitas Indonesia, Depok, Jawa Barat 16424, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2722-5763","authenticated-orcid":false,"given":"Hendri","family":"Murfi","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Universitas Indonesia, Depok, Jawa Barat 16424, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,28]]},"reference":[{"key":"ref_1","unstructured":"Van Rijmenam, M. (2019, October 30). A Short History of Big Data. Available online: https:\/\/datafloq.com\/read\/big-data-history\/239."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Chen, M., Mao, S., Zhang, Y., and Leung, V.C.M. (2014). Big Data: Related Technologies, Challenges and Future Prospects, Springer.","DOI":"10.1007\/978-3-319-06245-7"},{"key":"ref_3","unstructured":"Datameer (2019, October 25). Is the Hype Around Big Data Nothing But Hype. Available online: https:\/\/www.datameer.com\/blog\/big-data-hype-real-stay\/."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Zgurovsky, M.Z., and Zaychenko, Y.P. (2020). Big Data: Conceptual Analysis and Applications, Springer.","DOI":"10.1007\/978-3-030-14298-8"},{"key":"ref_5","unstructured":"Gantz, B.J., Reinsel, D., and Shadows, B.D. (2012). Big Data, Bigger Digital Shadows, and Biggest Growth in the Far East Executive Summary: A Universe of Opportunities and Challenges, IDC."},{"key":"ref_6","unstructured":"James, J. (2019, October 27). Data Never Sleeps 7. Domosphere. Available online: https:\/\/www.domo.com\/learn\/data-never-sleeps-7."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"652","DOI":"10.1109\/ACCESS.2014.2332453","article-title":"Toward Scalable Systems for Big Data Analytics: A Technology Tutorial","volume":"2","author":"Hu","year":"2014","journal-title":"IEEE Access"},{"key":"ref_8","first-page":"1","article-title":"Extracting Value from Chaos. 2011","volume":"1142","author":"Gatz","year":"2011","journal-title":"IDC iview"},{"key":"ref_9","first-page":"6","article-title":"3D Data Management: Controlling Data Volume, Velocity, and Variety. 2001","volume":"2001","author":"Laney","year":"2001","journal-title":"Gartner. Retrieved"},{"key":"ref_10","unstructured":"Shafer, T. (2019, October 20). The 42 V\u2019s of Big Data and Data Science. Available online: https:\/\/www.kdnuggets.com\/2017\/04\/42-vs-big-data-data-science.html."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1109\/JPROC.2015.2388958","article-title":"Big Data for Modern Industry: Challenges and Trends","volume":"103","author":"Yin","year":"2015","journal-title":"Proc. IEEE"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s42488-019-00001-2","article-title":"A Bibliometrics analysis on big data research (2009\u20132018)","volume":"1","author":"Xu","year":"2019","journal-title":"J. Data Inf. Manag."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1108\/CI-03-2018-0013","article-title":"Trending topics and themes in offsite construction(OSC) research: The application of topic modelling","volume":"19","author":"Liu","year":"2019","journal-title":"Constr. Innov."},{"key":"ref_14","unstructured":"Gl\u00e4nzel, W. (2003). Bibliometrics as a research field: A course on theory and application of bibliometric indicators, KU Leuven."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1007\/s11192-005-0208-0","article-title":"Combining full-text analysis and bibliometric indicators. A pilot study","volume":"63","author":"Glenisson","year":"2005","journal-title":"Scientometrics"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3362","DOI":"10.4028\/www.scientific.net\/AMM.284-287.3362","article-title":"Classification of Photovoltaic Research Papers by Using Text-Mining Techniques","volume":"284","author":"Lee","year":"2013","journal-title":"Appl. Mech. Mater."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1109\/TETC.2014.2330519","article-title":"A Survey of Clustering Algorithms for Big Data: Taxonomy & Empirical Analysis","volume":"2","author":"Fahad","year":"2014","journal-title":"IEEE Trans. Emerg. Top. Comput."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40537-017-0088-1","article-title":"A bibliometric approach to tracking big data research trends","volume":"4","author":"Kalantari","year":"2017","journal-title":"J. Big Data"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1007\/s11192-017-2383-1","article-title":"Discovering the interdisciplinary nature of Big Data research through social network analysis and visualization","volume":"112","author":"Hu","year":"2017","journal-title":"Scientometrics"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.csi.2017.01.004","article-title":"Research on Big Data\u2014A systematic mapping study","volume":"54","author":"Akoka","year":"2017","journal-title":"Comput. Stand. Interfaces"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Lu, L.Y.Y., and Liu, J.S. (2016, January 8\u201310). The major research themes of big data literature: From 2001 to 2016. Proceedings of the 2016 16th IEEE International Conference on Computer and Information Technology CIT, Nadi, Fiji.","DOI":"10.1109\/CIT.2016.46"},{"key":"ref_22","first-page":"795","article-title":"Discovering and forecasting interactions in big data research: A learning-enhanced bibliometric study","volume":"146","author":"Huang","year":"2018","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.techfore.2016.01.015","article-title":"Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research","volume":"105","author":"Zhang","year":"2016","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.ijmedinf.2016.11.006","article-title":"Visualizing the knowledge structure and evolution of big data research in healthcare informatics","volume":"98","author":"Gu","year":"2017","journal-title":"Int. J. Med. Inform."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1186\/s40537-016-0057-0","article-title":"Understanding big data themes from scientific biomedical literature through topic modeling","volume":"3","author":"Moerland","year":"2016","journal-title":"J. Big Data"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.iedeen.2017.06.002","article-title":"Research trends on Big Data in Marketing: A text mining and topic modeling based literature analysis","volume":"24","author":"Amado","year":"2018","journal-title":"Eur. Res. Manag. Bus. Econ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.jnca.2016.04.008","article-title":"A survey of big data management: Taxonomy and state-of-the-art","volume":"71","author":"Siddiqa","year":"2016","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.compind.2018.03.018","article-title":"Unfolding the relations between companies and technologies under the Big Data umbrella","volume":"99","author":"Canito","year":"2018","journal-title":"Comput. Ind."},{"key":"ref_29","unstructured":"(2019, December 24). An Introduction to Big Data Concepts and Terminology | DigitalOcean, 2016. Available online: https:\/\/www.digitalocean.com\/community\/tutorials\/an-introduction-to-big-data-concepts-and-terminology."},{"key":"ref_30","unstructured":"Marz, N., and Warren, J. (2015). Big Data: Principles and Best Practices of Scalable Realtime Data Systems, Manning Publications Co."},{"key":"ref_31","unstructured":"(2019, October 26). T-LAB Plus Quick Introduction. Available online: https:\/\/mytlab.com\/QIntroduction_en.pdf."},{"key":"ref_32","unstructured":"Scopus (2019, October 10). Why Choose Scopus; 2018. Available online: https:\/\/www.elsevier.com\/solutions\/scopus."},{"key":"ref_33","unstructured":"Harpring, P. (2010). Introduction to Controlled Vocabularies: Terminology for Art, Architecture, and Other Cultural Works, Getty Publications."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Medelyan, O., and Witten, I.H. (2006, January 11\u201315). Thesaurus based automatic keyphrase indexing. Proceedings of the ACM\/IEEE Joint Conference on Digital Libraries, Chapel Hill, NC, USA.","DOI":"10.1145\/1141753.1141819"},{"key":"ref_35","unstructured":"Medelyan, O. (2009). Human-Competitive Automatic Topic Indexing, The University of Waikato."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"He, G., Fang, J., Cui, H., Wu, C., and Lu, W. (2018, January 3\u20137). Keyphrase extraction based on prior knowledge. Proceedings of the ACM\/IEEE Joint Conference on Digital Libraries, Fort Worth, TX, USA.","DOI":"10.1145\/3197026.3203869"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.joi.2010.10.002","article-title":"An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field","volume":"5","author":"Cobo","year":"2011","journal-title":"J. Informetr."},{"key":"ref_38","first-page":"1275","article-title":"Some bibliometric procedures for analyzing and evaluating research fields","volume":"48","author":"Cobo","year":"2018","journal-title":"Appl. Intell."},{"key":"ref_39","unstructured":"Steinbach, M., Karypis, G., and Kumar, V. (2000, January 20\u201323). A Comparison of Document Clustering Techniques. Proceedings of the KDD-2000 Workshop on Text Mining, Boston, MA, USA."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Savaresi, S.M., and Boley, D.L. (2001, January 5\u20137). On the performance of bisecting K-means and PDDP. Proceedings of the 2001 SIAM International Conference on Data Mining, Chicago, IL, USA.","DOI":"10.1137\/1.9781611972719.5"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"345","DOI":"10.3233\/IDA-2004-8403","article-title":"A comparative analysis on the bisecting K-means and the PDDP clustering algorithms","volume":"8","author":"Savaresi","year":"2004","journal-title":"Intell. Data Anal."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/S0306-4573(02)00021-3","article-title":"An information-theoretic perspective of tf-idf measures","volume":"39","author":"Aizawa","year":"2003","journal-title":"Inf. Process. Manag."},{"key":"ref_43","unstructured":"Rish, I. (2001, January 4). An empirical study of the naive Bayes classifier. Proceedings of the IJCAI 2001 Workshop on Empirical Methods in Artificial Intelligence, Seattle, WA, USA."},{"key":"ref_44","unstructured":"Raschka, S. (2014). Naive Bayes and Text Classification I\u2014Introduction and Theory. arXiv."},{"key":"ref_45","unstructured":"Lancia, F. (2019, October 24). User Manual T-Lab 9.1. Tools for Text Analysis. Available online: https:\/\/www.mytlab.com\/Manual_en_plus.zip."},{"key":"ref_46","first-page":"327","article-title":"An introduction to applied correspondence analysis","volume":"45","author":"Groenen","year":"2000","journal-title":"PsycCRITIQUES"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2347","DOI":"10.1109\/COMST.2015.2444095","article-title":"Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications","volume":"17","author":"Guizani","year":"2015","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1165","DOI":"10.2307\/41703503","article-title":"Business intelligence and analytics: From big data to big impact","volume":"36","author":"Chen","year":"2012","journal-title":"MIS Q. Manag. Inf. Syst."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1109\/TKDE.2013.109","article-title":"Data mining with big data","volume":"26","author":"Wu","year":"2014","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.ins.2014.01.015","article-title":"Data-intensive applications, challenges, techniques and technologies: A survey on Big Data","volume":"275","author":"Chen","year":"2014","journal-title":"Inf. Sci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.ijinfomgt.2014.10.007","article-title":"Beyond the hype: Big data concepts, methods, and analytics","volume":"35","author":"Gandomi","year":"2015","journal-title":"Int. J. Inf. Manag."},{"key":"ref_52","first-page":"865","article-title":"Traffic flow prediction with big data: A deep learning approach","volume":"16","author":"Lv","year":"2014","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"678","DOI":"10.1109\/ACCESS.2015.2437951","article-title":"The internet of things for health care: A comprehensive survey","volume":"3","author":"Islam","year":"2015","journal-title":"IEEE Access"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"2227","DOI":"10.1109\/TPAMI.2014.2321376","article-title":"Scalable nearest neighbor algorithms for high dimensional data","volume":"36","author":"Muja","year":"2014","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts. Big Data Soc.","DOI":"10.1177\/2053951714528481"},{"key":"ref_56","unstructured":"Bagha, A., and Madisetti, V. (2016). Big Data Science & Analytics: A Hands-On Approach, VPT."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Said, A., and Torra, V. (2019). Data Science in Practice, Springer.","DOI":"10.1007\/978-3-319-97556-6"},{"key":"ref_58","unstructured":"Council, N.R. (2013). Frontiers in Massive Data Analysis, The National Academies Press."},{"key":"ref_59","unstructured":"Tozzi, C. (2019, October 10). 4 Big Data Infrastructure Pain Points and How to Solve Them. Available online: https:\/\/blog.syncsort.com\/2018\/11\/big-data\/4-big-data-infrastructure-points-solve\/."},{"key":"ref_60","unstructured":"Ardagna, C.A., and Damiani, E. (2014, January 16\u201317). Business Intelligence meets Big Data: An Overview on Security and Privacy. Proceedings of the NSF Workshop on Big Data Security and Privacy, Dallas, TX, USA."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1109\/CC.2014.7085614","article-title":"Big Data security and privacy: A review","volume":"11","author":"Matturdi","year":"2014","journal-title":"China Commun."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1109\/MNET.2014.6863131","article-title":"Toward efficient and privacy-preserving computing in big data era","volume":"28","author":"Lu","year":"2014","journal-title":"IEEE Netw."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1351","DOI":"10.1001\/jama.2013.393","article-title":"The inevitable application of big data to health care","volume":"309","author":"Murdoch","year":"2013","journal-title":"J. Am. Med. Assoc."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Zhao, W., Zou, W., and Chen, J.J. (2014). Topic modeling for cluster analysis of large biological and medical datasets. BMC Bioinform., 15.","DOI":"10.1186\/1471-2105-15-S11-S11"},{"key":"ref_65","unstructured":"Pr\u00f6llochs, N., and Feuerriegel, S. (2018). Business analytics for strategic management: Identifying and assessing corporate challenges via topic modeling. Inf. Manag."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1314","DOI":"10.1016\/j.eswa.2014.09.024","article-title":"Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation","volume":"42","author":"Moro","year":"2015","journal-title":"Expert Syst. Appl."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1","DOI":"10.15604\/ejef.2015.03.04.001","article-title":"The Power of Micro-Blogging: How to Use Twitter for Predicting the Stock Market","volume":"3","author":"Corea","year":"2015","journal-title":"Eurasian J. Econ. Financ."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.ijhm.2014.10.013","article-title":"What can big data and text analytics tell us about hotel guest experience and satisfaction?","volume":"44","author":"Xiang","year":"2015","journal-title":"Int. J. Hosp. Manag."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1016\/j.rser.2015.12.194","article-title":"A topic modeling based bibliometric exploration of hydropower research","volume":"57","author":"Jiang","year":"2016","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"937","DOI":"10.1016\/j.rser.2015.07.128","article-title":"Big Data issues and opportunities for electric utilities","volume":"52","author":"Barry","year":"2015","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_71","first-page":"1","article-title":"Big data and e-government: Issues, policies, and recommendations","volume":"19","author":"Bertot","year":"2013","journal-title":"ACM Int. Conf. Proc. Ser."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"5","DOI":"10.3233\/IP-140328","article-title":"Big data, open government and e-government: Issues, policies and recommendations","volume":"19","author":"Bertot","year":"2014","journal-title":"Inf. Polity"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1145\/2500873","article-title":"Big Data Applications in the Government","volume":"57","author":"Kim","year":"2014","journal-title":"Commun. ACM"},{"key":"ref_74","first-page":"1","article-title":"Big Data for Digital Government","volume":"1","author":"Chen","year":"2014","journal-title":"Int. J. Public Adm. Digit. Age"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1177\/0950422218770937","article-title":"Opportunities and challenges for big data analytics in US higher education: A conceptual model for implementation","volume":"32","author":"Attaran","year":"2018","journal-title":"Ind. High. Educ."},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Riffai, M.M.M.A., Duncan, P., Edgar, D., and Al-Bulushi, A.H. (2016, January 15\u201316). The potential for big data to enhance the higher education sector in Oman. Proceedings of the 2016 ICBDSC 3rd MEC International Conference on Big Data and Smart City, Muscat, Oman.","DOI":"10.1109\/ICBDSC.2016.7460346"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1007\/s11528-016-0072-1","article-title":"Big Opportunities and Big Concerns of Big Data in Education","volume":"60","author":"Wang","year":"2016","journal-title":"TechTrends"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1016\/j.trc.2018.03.010","article-title":"Recent applications of big data analytics in railway transportation systems: A survey","volume":"90","author":"Ghofrani","year":"2018","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"1099","DOI":"10.1016\/j.asoc.2015.06.006","article-title":"Soft computing in big data intelligent transportation systems","volume":"38","author":"Wang","year":"2016","journal-title":"Appl. Soft Comput. J."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"620","DOI":"10.1109\/TITS.2015.2480157","article-title":"Big data for social transportation","volume":"17","author":"Zheng","year":"2015","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_81","unstructured":"Clemment, J. (2019, December 27). \u201cGlobal social media ranking 2019\u201d, Statista, 2019. Available online: https:\/\/www.statista.com\/statistics\/272014\/global-social-networks-ranked-by-number-of-users\/."},{"key":"ref_82","unstructured":"Mell, P., and Grance, T. (2019, October 17). The NIST-National Institute of Standars and Technology- Definition of Cloud Computing, Available online: https:\/\/csrc.nist.gov\/publications\/detail\/sp\/800-145\/final."},{"key":"ref_83","doi-asserted-by":"crossref","unstructured":"Mittal, M., Balas, V.E., Goyal, L.M., and Kumar, R. (2019). Big Data Processing Using Spark in Cloud, Springer.","DOI":"10.1007\/978-981-13-0550-4"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"34","DOI":"10.3991\/ijim.v11i2.6561","article-title":"Big data and cloud computing: Trends and challenges","volume":"11","author":"Abdelfattah","year":"2017","journal-title":"Int. J. Interact. Mob. Technol."},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"Srinivasan, S. (2018). Guide to Big Data Applications, Springer.","DOI":"10.1007\/978-3-319-53817-4"},{"key":"ref_86","unstructured":"Jamali, M.A.J., Bahrami, B., Heidari, A., Allahverdizadeh, P., and Norouzi, F. (2019). Towards the Internet of Things, Springer."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1016\/j.comnet.2017.06.013","article-title":"The role of big data analytics in Internet of Things","volume":"129","author":"Ahmed","year":"2017","journal-title":"Comput. Netw."},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Xu, X., Huang, S., Chen, Y., Brown, K., Halilovic, I., and Lu, W.T. (July, January 27). SAaaS: Time series analytics as a service on IoT. Proceedings of the 2014 ICWS IEEE International Conference on Web Services, Anchorage, AK, USA.","DOI":"10.1109\/ICWS.2014.45"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1016\/j.techfore.2019.01.012","article-title":"Forecasting technology trends using text mining of the gaps between science and technology: The case of perovskite solar cell technology","volume":"146","author":"Li","year":"2019","journal-title":"Technol. Forecast. Soc. Change"},{"key":"ref_90","unstructured":"Mistrik, I., Bahsoon, R., Ali, N., Heisel, M., and Maxim, B. (2017). Software Architecture for Big Data and the Cloud, Morgan Kaufmann."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/11\/2\/69\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T14:08:45Z","timestamp":1760364525000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/11\/2\/69"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,28]]},"references-count":90,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2020,2]]}},"alternative-id":["info11020069"],"URL":"https:\/\/doi.org\/10.3390\/info11020069","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,1,28]]}}}