SENTIMENT ANALYSIS ON SOCIAL NETWORK USING TWITTER DATASETS

Abstract
This research presents a unique software based on the programming language Twitter API and R. Twitter keywords are searched to get relevant tweets. Twitter APIs and Rs programming may extract these rich-opinion data sets about the contents of tweets, tweet writers, and tweets. This program has been expanded to geographical location search and post-time search in order to gather more complete Twitter feelings about political and economic problems. A new text preprocessing technique is suggested and being explored for Twitter data. The tweets collected may include a range of information about interference in many languages. This research presented for the first time a hybrid model for the categorization of Twitter sentiment. The performance of the Twitter polarity classification will be improved by combining it with a new feature chosen method based on the NRC lexicon and the classic classification algorithms KNN and Nave Bayes. The findings are assessed and verified.

Authors
K Karthick
St. Jerome's College of Arts and Science, India

Keywords
Optimization, Natural Language Processing, Twitter Datasets, Sentiment Analysis
Published By :
ICTACT
Published In :
ICTACT Journal on Data Science and Machine Learning
( Volume: 2 , Issue: 3 )
Date of Publication :
June 2021

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