An NLP Technique on Sentiment Analysis
Aadesh Attri1, Alok Rai2, Yash Malhotra3
1Aadesh Attri, Department Computer Science Engineering, Galgotias University, Greater Noida (Uttar Pradesh), India.
2Alok Rai, Department Computer Science Engineering, Galgotias University, Greater Noida (Uttar Pradesh), India.
3Yash Malhotra, Department Computer Science Engineering, Galgotias University, Greater Noida (Uttar Pradesh), India.
Manuscript received on 30 June 2023 | Revised Manuscript received on 23 July 2023 | Manuscript Accepted on 15 February 2024 | Manuscript published on 28 February 2024 | PP: 28-31 | Volume-13 Issue-3, February 2024 | Retrieval Number: 100.1/ijitee.H96790712823 | DOI: 10.35940/ijitee.H9679.13030224
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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: We need to structure the data provided by Twitter social media for accurate analysis and derive meaningful insights from it. We will analyse the sentiment behind a user’s comment on Twitter to determine the meaning of the text. To identify the negative emotions expressed in the text, we will utilise various algorithms to discern the underlying intention. To address this kind of issue, estimation investigation and deep learning methods are two complementary approaches. We are using Naive Bayes algorithms, SVM (Support Vector Machine) and other classification algorithms to get our required output [1].These are known as deep learning or machine learning methods for extracting emotions from sentences. At the end of the process, we will obtain the desired output and verify its accuracy accordingly.
Keywords: Support Vector Machine, Deep Learning /Machine Learning, social media
Scope of the Article: Deep Learning