Sentiment Analysis of Text using Rule Based and Natural language Toolkit
Madhav Singh Solanki
Madhav Singh Solanki, Department of Computer Science and Engineering, Sanskriti University, (Uttar Pradesh), India.
Manuscript received on 05 October 2019 | Revised Manuscript received on 19 October 2019 | Manuscript Published on 26 December 2019 | PP: 164-168 | Volume-8 Issue-12S October 2019 | Retrieval Number: L104910812S19/2019©BEIESP | DOI: 10.35940/ijitee.L1049.10812S19
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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: Analysis of sentiment or opinion is one of the computational studies of the human kind’s written opinions, feelings, attitudes, emotions. It is one of the most active fields of research in the area of natural language processing and text mining in the past few years and it has been popular for its wide range of applications because opinions are central to almost all human activities and are key drivers of our behavior. Part of the reason for the lack of the previous study was that in digital forms there was little opinionated text. So it’s no surprise that the field coin starts and grows swiftly. Coincide with the web social media. In fact, research has expanded beyond computer science into management science and social sciences, given its importance to the enterprise and society in general. This paper shows the sentimental analysis process by Natural Language Toolkit and Python Libraries to find the hidden meaning in the unstructured data.
Keywords: Sentiment Analysis; Machine Learning; Opinion Mining; Python; Text Analytics.
Scope of the Article: Natural Language Processing