Twitter Data Analysis on Natural Disaster Management System

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2017 by IJETT Journal
Volume-45 Number-8
Year of Publication : 2017
Authors : M.V.Sangameswar, Dr. M.Nagabhushana Rao, N.S.Murthy
  10.14445/22315381/IJETT-V45P273

MLA 

M.V.Sangameswar, Dr. M.Nagabhushana Rao, N.S.Murthy " Twitter Data Analysis on Natural Disaster Management System ", International Journal of Engineering Trends and Technology (IJETT), V45(7),345-350 March 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
The objective of this paper is to comprehensively study the Data Structure Alignment in order to maximize storage potential and to provide for fast and efficient memory access. Aligning data elements allows the processor to fetch data from memory in an efficient manner and thereby improves performance. Alignment refers to the arrangement of data in memory and deals with the issue of accessing data in chunks of fixed size from the main memory.

 References

[1] Sunil B. Mane , Sunil B. Mane, Yashwant Sawant, Saif Kazi, Vaibhav Shinde , “Real Time Sentiment Analysis of Twitter Data Using Hadoop”, (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (3) , 2014, 3098 – 3100 , ISSN:0975-9646.
[2] Mahalakshmi R, Suseela S , “Big-SoSA:Social Sentiment Analysis and Data Visualization on Big Data”, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 4, Issue 4, April 2015 , pp 304-306, ISSN : 2278-1021.
[3] Matthew Koehler, Spencer Greenhalgh, Andrea Zellner, Michigan State University, United States , “Potential Applications of Sentiment Analysis in Educational Research and Practice – Is SITE the Friendliest Conference?”, Mar 02, 2015 in Las Vegas, NV, United States ISBN 978-1-939797-13-1 Publisher: Association for the Advancement of Computing in Education (AACE).
[4] Ramesh R, Divya G, Divya D, Merin K Kurian , “Big Data Sentiment Analysis using Hadoop “, (IJIRST )International Journal for Innovative Research in Science & Technology,Volume 1 , Issue 11 , April 2015 ISSN : 2349-6010.
[5] Peiman Barnaghi, Parsa Ghaffari, John G. Breslin , “Text Analysis and Sentiment Polarity on FIFA World Cup 2014 Tweets” , Conference ACM SIGKDD’15, August 10-13, 2015, Sydney, Australia. Copyright 2015 ACM 1-58113-000-0/08/2015.
[6] “Mining Data from Twitter” from AbhishangaUpadhyay, Luis Mao, Malavika Goda Krishna ( PDF)
[7] G.Vinodhini , RM.Chandrasekaran, “Sentiment Analysis and Opinion Mining: A Survey” , International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 6, June 2012 ISSN: 2277 128X.
[8] Michael G. Noll, Applied Research, Big Data, Distributed Systems, Open Source, "Running Hadoop on Ubuntu Linux (Single-Node Cluster)", [online], available at http://www.michael-noll.com/tutorials/running-hadoop-on-ubuntu-linux-single-node-cluster/
[9] "Install Apache Hadoop 2.6.0 in Ubuntu (Multi node/Cluster setup)", [online], available at http://pingax.com/install-apache-hadoop-ubuntu-cluster-setup/
[10] Aditya B. Patel, Manashvi Birla, Ushma Nair, "Addressing Big Data Problem Using Hadoop and Map Reduce",6-8 Dec. 2012.
[11] https://blog.cloudera.com/blog/ 2012/11/analyz ing-twitter-data-with-hadoop-part-3-querying-semi-structured-data-with-hive/
[12] "Application Programming Interface."Wikipedia . Wikimedia Foundation, 23 Oct. 2014. Web. 24 Oct. 2014.
[13] "Twitter's API --‐HowStuffWorks."HowStuffWorks. N.p., n.d. Web. 24 Oct. 2014.
[14] Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More-Matthew A. Russell [15] "The Streaming APIs."Twitter Developers. N.p., n.d. Web. 23 Oct. 2014.
[16] Sangeeta, Twitter Data Analysis Using FLUME & HIVE on Hadoop FrameWorkSpecial Issue on International Journal of Recent Advances in Engineering & Technology (IJRAET) V-4 I-2 For National Conference on Recent Innovations in Science, Technology & Management (NCRISTM), 26th to 27th February 2016.
[17] A. Bifet and E. Frank, "Sentiment knowledge discovery in twitter streaming data," in Discovery Science, 2010, pp. 1-15.
[18] T. Blog, "Insights into the #WorldCup conversation on Twitter," in Twitter Blog, ed, 2014.
[19] S. Sinha, C. Dyer, K. Gimpel, and N. A. Smith, "Predicting the NFL using Twitter," arXiv preprint arXiv:1310.6998, 2013.
[20] P. Priyanthan, B. Gokulakrishnan, T. Ragavan, N. Prasath, and A. S. Perera, "Opinion mining and sentiment analysis on a twitter data stream," ICTer 2012, 2012.
[21] D. Terrana, A. Augello, and G. Pilato, "Automatic Unsupervised Polarity Detection on a Twitter Data Stream," in Semantic Computing (ICSC), 2014 IEEE International Conference on , 2014, pp. 128 -134.
[22] L. Zhang, "Sentiment analysis on Twitter with stock price and significant keyword correlation," 2013.
[23] M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. H. Witten, "The WEKA data mining software: an update," ACM SIGKDD explorations newsletter, vol. 11, pp. 10 -18, 2009

Keywords
Big Data, Apache Hadoop, MapReduce, HDFS, FLUME, HIVE and Twitter