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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM64091
Volume:
10 |
5 |
May 2026
Pages:
1-4
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Compuer Science
Ayya Nadar Janaki Ammal College, Sivakasi
Department of Compuer Science
Ayya Nadar Janaki Ammal College, Sivakasi
The expansion of Technology has modified the means of expressing people’s opinions, views and Sentiments concerning specific product,services,people and a lot of, by victimization social media services like Facebook,Instagram and Twitter. because of this is often massiveamount of knowledge gets generated. to seek out insights from this information generated and confirm call we tend to implement net application that collects twitter information and shows it in several applied math forms. the most objective of the work bestowed inside this paper was to style and implement twitter information analysis and mental image in R platform. Our primary approach was to concentrate on time period analysis instead of historic datasets. Twitter API leave collection the feelings data within the style of either positive score, negative score or neutral. Then we tend to determined to make our back-end on high of Hadoop platform which incorporates Hadoop HDFS as distributed filing system and Map-reduce as distributed computation. Package twitteR permits to use totally different twitter perform. Hadoop provides integration with R called RHadoop, itprovides totally different packages wont to connect R setting to Hadoop and to perform the analysis of tweets information that are having a size of GB s .To Visualize information we tend to used Rshiny application that usually helps to represent information simply.
KEYWORDS
The main objective of this paper was to explain and style system for twitter information analysis and mental image. It was developed victimization R and also the huge processing technologies called Hadoop. totally different RHadoop packages were wont to process great deal of knowledge and to support distributed processing in R. we tend to developed a group of analytical representation that helps user to spot product people,services and films information and might gain insights from it. we tend to took a group of visualizations, implemented in Shiny net applications that helps to integrate computer program with RHadoop. RHadoop functions were used and used in varied preprocessing, data cleaning and querying strategies.
[1] R Graphics Cookbook Practical Recipes for Visualizing Data By Winston chang. [2] Learn Ggplot2 Using Shiny App Book by Keon-Woong Moon. [3] Web Application Development With R Using Shiny Chris Beeley. [4] The R Book Book by Michael J Crawley. [5] A Handbook of Statistical Analyses Using R Book by Brian Everitt and Torsten Hothorn. [6] Statistical Analysis with R Book by John M. Quick. [7] https://www.r-bloggers.com/integrating-r-with-apachehadoop/. [8] http://blog.revolutionanalytics.com/2015/06/using-hado op-with-r-it-depends.html. [9] http://stackoverflow.com/questions/33046510/r-hadoop -integration-how-to-connect-r-to-remote-hdfs. [10]http://stackoverflow.com/questions/23828643/rstudio-connect-to-remote-hadoop-server.
Publication Date
5/26/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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