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international journal of computer techniques(ijct)

Paper Title : EVENT BASED SENTIMENT ANALYSIS ON TWITTER USING MACHINE LEARNING ALGORITHMS

ISSN : 2394-2231
Year of Publication : 2021

10.29126/23942231/IJCT-v8i3p8
Authors: Ashwini Bagade, Piyush Jadhav, Omkar Yelpale, Piyush Kulkarni

MLA Style: Ashwini Bagade, Piyush Jadhav, Omkar Yelpale, Piyush Kulkarni " EVENT BASED SENTIMENT ANALYSIS ON TWITTER USING MACHINE LEARNING ALGORITHMS " Volume 8 - Issue 3 May-June , 2021 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org

APA Style: Ashwini Bagade, Piyush Jadhav, Omkar Yelpale, Piyush Kulkarni " EVENT BASED SENTIMENT ANALYSIS ON TWITTER USING MACHINE LEARNING ALGORITHMS " Volume 8 - Issue 3 May-June , 2021 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org

Abstract
This project addresses the problem of sentiment analysis in twitter; that is classifying tweets according to the sentiment expressed in them: positive, negative or neutral. Twitter is an online micro- blogging and social-networking platform which allows users to write short status updates of maximum length 140 characters. It is a rapidly expanding service with over 200 million registered users out of which 100 million are active users and half of them log on twitter on a daily basis – generating nearly 250 million tweets per day. Due to this large amount of usage we hope to achieve a reflection of public sentiment by analysing the sentiments expressed in the tweets. Analysing the public sentiment is important for many applications such as firms trying to find out the response of their products in the market, predicting political elections and predicting socioeconomic phenomena like stock exchange. The aim of this project is to develop a functional classifier for accurate and automatic sentiment classification of an unknown tweet stream for analysing the particular . In this project we have used the python library to stream the live raw data from the twitter and we will combine it with the standardised dataset. Then using some Machine Learning algorithms we will carry out the sentiment analysis. This project targets the tweets about the specific event so it will be helpful to use this project analyse the impact ofthat event over the social media

Reference
[1] “Liza Mikarsa, Sherly Novianti Thahir, "A Text Mining Application of Emotion Classifications of Twitter’s user using Naïve Bayes Method", IEEE,2015” [2] Shikha Tiwari,Anshika Verma et al“"Social Media Sentiment Analysis Twitter Datasets "ICACCS 2020” [3] Vishal A. Kharde ,S.S. Sonawane “Sentiment Analysis of Twitter Data: A Survey of Techniques IJCA 2016” [4] Bhawani Selvaretnam et al “Natural Language Processing for Sentiment Analysis. International Conference on Artificial Intelligence with Applications in Engineering and Technology 2014” [5] Pouria Kaviani, Mrs. Sunita Dhotre “Short Survey on Naive Bayes Algorithm. International Journal of Advance Engineering and Research Development 2017” [6]Radhi D. Desai “Sentiment Analysis of Twitter Data IEEE 2018” [7]https://www.wikipedia.org

Keywords
—NLP, Machine Learning, Naive Bayes, Precision, Recall,f1-score.

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