Data Mining and Machine Learning: Design a Generalized Real Time Sentiment Analysis System on Tweeter Data Using Natural Language Processing
Jitendra Soni1, Kirti Mathur2
1Jitendra Soni, Institute of Engineering & Technology, DAVV, Indore (M.P.), India
2Dr. Kirti Mathur, International Institute of Professional Studies, DAVV, Indore (M.P.), India
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 2139-2142 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8492088619/2019©BEIESP | DOI: 10.35940/ijeat.F8492.088619
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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: Sentiment analysis is a task, that is becoming recently important for numerous companies. Because the consigner subscriptions on social media like Facebook, twitter and other side get their product reviews. If the company wants to track tweets about their brand to command over the impact on time or many website analyze the comments on their articles. This will help them to track comments and impact. So the sentiment analysis is an automated system that collects and analyzes the content and generates the desired results. This paper proposes a sentiment analysis system for twitter posts. Proposed system will work on real time tweets. System is also designed in such a way that this can analyze data related to any topic. Python programming language is used to extract tweets form twitter feeds. Proposed system also calculates the level of sentiments. That how much negative or positive tweets are. This paper also presents some real time result analysis.
Keywords: API, Lexican, Machine Learning, NLP, Python, Sentiment Analysis, Tweepy.