Twitter-Sentiment-Analysis

Abstract

💠In recent days with the explosion of Big Data there is a large demand for organisations and data scientists to perform information extraction using non-traditional sources of data.

💠Twitter is one of the non-traditional data sources with unlimited potential. It contains a large reserve of data sets

💠One of the available tools is twitter API which lets us collect data and various other information about the tweets

💠With use of this API we can collect data related to an specific domain and create an CNN model for it.

✴️ Sentiment analysis, also referred to as opinion mining, is an approach to natural language processing (NLP) that identifies the emotional tone behind a body of text. This is a popular way for organizations to determine and categorize opinions about a product, service, or idea.

Importance of Sentiment Analysis

Applications that uses twitter sentiment analysis are :

1.Social Media Monitoring 

2.Customer Service 

3.Market Research 

4.Brand Monitoring

Process Overview

Result and Discussion

Publications

Convolution Neural Networks Machine Learning model to classify the polarity of a tweet using Gensim Word2VecConvolution Neural Networks Machine Learning model to classify the polarity of a tweet using Gensim Word2Vec IEEE · Feb 2, 2023

https://ieeexplore.ieee.org/document/10028933