Framework for Sentimental Analysis of Twitter Data

Authors(4) :-B. U. Anubharathi, Aishwarya V, S. Aparna, S. Divyaalakshmi

Twitter like Micro-blogging sites has become a wide space for individuals or organizations across the globe to express their views and experience in the form of tweets. The surge of data can be processed using Data mining to obtain further understanding about the public opinions. sentimental analysis is used here to search needs by detecting opinions or emotions from the twitter data. Our results show the cleaned texts of individual tweets using R. Sentimental analysis of any keyword that is given by user is processed. Sentimental analysis used here is helpful in binary classification of tweets i.e. Classification of tweets into positive and negative. Consolidated to this we also analyse Multiple sentiments of the tweets. We likewise break down most extreme recurrence of catchphrase utilized in the tweets and its users. Trending hashtags according to location using location ID and pattern match technique is utilized in finding the recurrence of hashtags utilized in a tweet of explicit end client.

Authors and Affiliations

B. U. Anubharathi
Assistant Professor(SS), Department of Computer Science and Engineering, Rajalakshmi Engineering College, Thandalam,Tamil Nadu, India
Aishwarya V
Department of Computer Science, Rajalakshmi Engineering College(Anna university),Thandalam,Tamil Nadu, India
S. Aparna
Department of Computer Science, Rajalakshmi Engineering College(Anna university),Thandalam,Tamil Nadu, India
S. Divyaalakshmi
Department of Computer Science, Rajalakshmi Engineering College(Anna university),Thandalam,Tamil Nadu, India

Datamining, Social media, Twitter, Sentimental analysis, Twitter APIs

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Publication Details

Published in : Volume 5 | Issue 2 | March-April 2019
Date of Publication : 2019-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 345-354
Manuscript Number : CSEIT1195258
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

B. U. Anubharathi, Aishwarya V, S. Aparna, S. Divyaalakshmi, "Framework for Sentimental Analysis of Twitter Data", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.345-354, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT195258
Journal URL : http://ijsrcseit.com/CSEIT1195258

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