Open AccessExtraction and Analyze Text in Twitter using Naive Bayes Technique.
Author(s) -
Ameen Abdullah Qaid Aqlan,
B. Manjula
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.d1568.029420
Subject(s) - naive bayes classifier , sentiment analysis , product (mathematics) , feeling , computer science , sorting , social media , recall , data science , information retrieval , artificial intelligence , advertising , world wide web , internet privacy , psychology , support vector machine , mathematics , social psychology , business , cognitive psychology , algorithm , geometry
there are several topics and areas that are at an advanced stage of interest and research around the world because of their importance and usefulness to humanity, including the sentiment analysis. By studding of sentiment analysis (SA), one can learn about the mysterious things and different feelings of others. The purpose of all of this is to know the pros and cons about a product or anything else and correct the negatives in future that are found. In our research, we have benefited from social media sites, especially Twitter, in collecting data about the iPhone 11 product to see how satisfied customers are about this product. We collected a lot of different opinions using API and then transferred them to an information bank. In our research we used the famous Naive Bayes (NB) algorithm and had an active role in classifying reviews and sorting them and knowing the pros and cons, where we got good results compared to previous works which are as follows: precision 80, recall 83, f1 score 81, accuracy 80.25.