COVID19 SENTIMENT ANALYSIS FOR A LARGE SCALE BENCHMARK TWITTER DATA SET
Author(s):
Mamidi Prathima Deva Sena, Dr. G. Babu Rao
Keywords:
Abstract
Sentiment analysis over Twitter offer formation a fast and effective way to monitor the publics’ feelings towards their brand, business, directors, etc. A wide range of characteristic and methods for training sentiment classifiers for Twitter datasets have been researched in recent years with varying results.Twitter offers formations a fast and productive way to analyse customers' perspectives toward the critical to success in the market place. Expanding a program for sentiment analysis is an approach to be used to reckoning measure customers' perceptions. Sentiment analysis is also known as “opinion mining” or “emotion Artificial Intelligence” and suggests to the utilization of natural language processing (NLP), text mining, computational linguistics, and bio measurements to methodically recognize, calculate, evaluate, and examine emotional states and subjective information. The system is developed, the dataset was collected from twitter. The employees work from home tweets dataset as input was collected from twitter by using API key. Then, we have to analyse the sentiment by using the NLP techniques, text classification and deep learning algorithm. The experimental results shows that, the performance metrics such as accuracy and analyse the sentiment based on sentiment analyser into positive, negative and neutral.
Article Details
Unique Paper ID: 155233

Publication Volume & Issue: Volume 9, Issue 1

Page(s): 252 - 254
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