Extraction and Analyze Text in Twitter using Naive Bayes Technique
Ameen Abdullah Qaid Aqlan1, B.Manjula2
1Ameen Abdullah Qaid Aqlan*, Department of Computer Science, Kakatiya University, Warangal, Telangana, India.
2B.Manjula, Department of Computer Science, Kakatiya University, Warangal, Telangana, India.
Manuscript received on January 11, 2020. | Revised Manuscript received on January 20, 2020. | Manuscript published on February 10, 2020. | PP: 1635-1639 | Volume-9 Issue-4, February 2020. | Retrieval Number: D1568029420/2020©BEIESP | DOI: 10.35940/ijitee.D1568.029420
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Sentiment Analysis, Data Mining, Classification Reviews, NB Algorithm, Twitter.
Scope of the Article: Data Mining