Open AccessSentiment Analysis on Twitter Airline Data
Author(s) -
Kriti Jain
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.35807
Subject(s) - sentiment analysis , polarity (international relations) , computer science , task (project management) , feeling , social media , natural language processing , artificial intelligence , information retrieval , data science , world wide web , psychology , social psychology , genetics , management , cell , economics , biology
Sentiment analysis, also known as sentiment mining, is a submachine learning task where we want to determine the overall sentiment of a particular document. With machine learning and natural language processing (NLP), we can extract the information of a text and try to classify it as positive, neutral, or negative according to its polarity. In this project, We are trying to classify Twitter tweets into positive, negative, and neutral sentiments by building a model based on probabilities. Twitter is a blogging website where people can quickly and spontaneously share their feelings by sending tweets limited to 140 characters. Because of its use of Twitter, it is a perfect source of data to get the latest general opinion on anything.