Open Access
SHS Web Conf.
Volume 119, 2021
3rd International Conference on Quantitative and Qualitative Methods for Social Sciences (QQR’21)
Article Number 07006
Number of page(s) 7
Section Technology and Society / Covid-19 Innovations
Published online 24 August 2021
  1. P.B. Makeshwar, A. Kalra, N.S. Rajput, K.P. Singh, Computational Scalability with Apache Flume and Mahout for Large Scale Round the Clock Analysis of Sensor Network Data, 6, 3 (2015) [Google Scholar]
  2. A. Hasan, S. Moin, A. Karim, S. Shamshirband, Machine Learning-Based Sentiment Analysis for Twitter Accounts, 15, 3 (2018) [Google Scholar]
  3. E. Gallinucci, M. Golfarelli, S. Rizzi, Advanced topic modelling for social business intelligence, 20, 14 (2015) [Google Scholar]
  4. R. Wrembe, Data Warehouses and Olap: Concepts, Architectures and Solutions, 332, 217, December 2006, Paris, France (2006) [Google Scholar]
  5. R. Berlanga, L. Garcia-Moya, V. Nebot, M.J. Aramburu, I. Sanz, D.M. Llido, SLOD-BI: An Open Data Infrastructure for Enabling Social Business Intelligence, 28, 3 (2015) [Google Scholar]
  6. I. Paik, T. Golfarelli, H. Tanaka, H. Ohashi, C. Chen, Big data infrastructure for active situation awareness on social network services, 2, 1 (2013) [Google Scholar]
  7. H. Han, W. Yonggang, C. Tat-Seng, L. Xuelong, Toward Scalable Systems for Big Data Analytics: A Technology Tutorial, 36, 6 (2014) [Google Scholar]
  8. A. Meier, M. Kaufmann, SQL & NoSQL Databases, Models, Languages, Consistency Options and Architectures for Big Data Management, 218, 169 (2019) [Google Scholar]
  9. L. Schlesinger, F. Irmert, W. Lehner, Supporting the ETL-process by Web Service technologies, 17, 9 (2005) [Google Scholar]
  10. F. Laghaei, O. Bin Ibrahim, Using Social Network’s Data By Extraction Transformation Loading (ETL), 11, 4 (2017) [Google Scholar]
  11. Y. Lu, F. Wang, R. Maciejewski, Business Intelligence from Social Media: A Study from the VAST Box Office Challenge, 11, 5 (2018) [Google Scholar]
  12. F. Sebastiani, Machine Learning in Automated Text Categorization, 47, 34 (2002) [Google Scholar]
  13. W. Sherchan, S. Nepal, C. Paris, A Survey of Trust in Social Networks, 33, 19 (2013) [Google Scholar]

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