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Research Article

Real-time Twitter data analysis using Hadoop ecosystem

& | (Reviewing editor)
Article: 1534519 | Received 04 Mar 2018, Accepted 07 Oct 2018, Published online: 19 Oct 2018

References

  • Barskar, A. , & Phulre, A. (2017). Opinion mining of twitter data using Hadoop and Apache Pig. International Journal of Computer Applications , 158, 9. doi:10.5120/ijca2017912854
  • Bhardwaj, A. , Kumar, A. , Narayan, Y. , & Kumar, P. (2015, December). Big data emerging technologies: A case study with analyzing twitter data using apache hive. In Recent Advances in Engineering & Computational Sciences (RAECS), 2015 2nd International Conference on (pp. 1–6). Chandigarh: IEEE.
  • Chauhan, V. , & Shukla, A. (2017, April). Sentimental analysis of social networks using MapReduce and big data technologies. International Journal of Computer Science and Network , 6(2), 120–13.
  • Ennaji, F. Z. , El Fazziki, A. , Sadgal, M. , & Benslimane, D. (2015, November). Social intelligence framework: Extracting and analyzing opinions for social CRM. In Computer Systems and Applications (AICCSA), 2015 IEEE/ACS 12th International Conference of (pp. 1–7). Marrakech, Morocco: IEEE.
  • Fernandes, R. , & Rio D’Souza, G. L. (2017). Semantic analysis of reviews provided by mobile web services using rule based and supervised machine learning techniques. International Journal of Applied Engineering Research , 12(22), 12637–12644.
  • González-Ibánez, R. , Muresan, S. , & Wacholder, N. (2011, June). Identifying sarcasm in twitter: A closer look. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Short Papers-volume2 (pp. 581–586), Portland, Oregon.
  • Ha, I. , Back, B. , & Ahn, B. (2015). MapReduce functions to analyze sentiment information from social big data. International Journal of Distributed Sensor Networks , 11, 417502. doi:10.1155/2015/417502
  • Jain, A. , & Bhatnagar, V. (2016). Crime data analysis using pig with Hadoop. Procedia Computer Science , 78, 571–578. doi:10.1016/j.procs.2016.02.104
  • KadharBasha, J. , & Balamurugan, M. (2017, May). A review on Hive and Pig. International Journal of Advanced Research in Basic Engineering Sciences and Technology , 3(39), 53–58.
  • Khade, A. A. (2016). Performing customer behavior analysis using big data analytics. Procedia Computer Science , 79, 986–992. doi:10.1016/j.procs.2016.03.125
  • Kumar, M. , & Bala, A. (2016, March). Analyzing twitter sentiments through big data. In Computing for Sustainable Global Development (INDIACom), 2016 3rd International Conference on (pp. 2628–2631). New Delhi, India: IEEE.
  • Nadagoud, M. S. , & Naik, M. K. D. (2015, May). Market sentiment analysis for popularity of Flipkart. International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) , 4(5), 2117–2123.
  • Riloff, E. , Qadir, A. , Surve, P. , De Silva, L. , Gilbert, N. , & Huang, R. (2013, October). Sarcasm as contrast between a positive sentiment and negative situation. EMNLP , 13, 704–714.
  • Sangeeta . (2016, February). Twitter data analysis using Flume & Hive on Hadoop frame work. International Journal of Recent Advances in Engineering & Technology , V4, I–2.
  • Selvan, L. G. S. , & Moh, T. S. (2015, June). A framework for fast-feedback opinion mining on Twitter data streams. In Collaboration Technologies and Systems (CTS), 2015 International Conference on (pp. 314–318). Atlanta, GA, USA: IEEE.
  • Shang, S. , Shi, M. , Shang, W. , & Hong, Z. (2015, June). Research on public opinion based on big data. In Computer and Information Science (ICIS), 2015 IEEE/ACIS 14th International Conference on (pp. 559–562). Las Vegas, NV, USA: IEEE.
  • Sheela, L. J. (2016). A review of sentiment analysis in twitter data using Hadoop. International Journal of Database Theory and Application , 9(1), 77–86. doi:10.14257/ijdta
  • Shrote, K. R. , & Deorankar, A. V. (2016, February). Review based service recommendation for big data. In Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), 2016 2nd International Conference on (pp. 470–474). Chennai, India: IEEE.
  • Tare, M. , Gohokar, I. , Sable, J. , Paratwar, D. , & Wajgi, R. (2014). Multi-class tweet categorization using map reduce paradigm. International Journal of Computer Trends and Technology (IJCTT) , 9(2), 78–81. doi:10.14445/22312803/IJCTT-V9P117
  • Verma, J. P. , Patel, B. , & Patel, A. (2015, February). Big data analysis: Recommendation system with Hadoop framework. In Computational Intelligence & Communication Technology (CICT), 2015 IEEE International Conference on (pp. 92–97). Ghaziabad, India: IEEE. doi:10.1002/mus.24271
  • Yadav, K. , Pandey, M. , & Rautaray, S. S. (2016, November). Feedback analysis using big data tools. In ICT in Business Industry & Government (ICTBIG), international conference on (pp. 1–5). Indore, India: IEEE.