Sentimental Analysis in Twitter Using Python

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Year : July 6, 2023 | Volume : 01 | Issue : 01 | Page : 28-32

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Rukmini Ankush Dhamdhere, Nikita Makarand Dhumal, Mayuri Keshav Gawali, Ganesh Pramod Kulkarni

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    1. Student, Student, Student, Student,Department of Information Technology, NBN Sinhgad School of Engineering, Pune, Department of Information Technology, NBN Sinhgad School of Engineering, Pune, Department of Information Technology, NBN Sinhgad School of Engineering, Pune, Department of Information Technology, NBN Sinhgad School of Engineering, Pune,Maharashtra, Maharashtra, Maharashtra, Maharashtra,India, India, India, India

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    Abstract

    n Social media websites are a great source of information because they have a lot of data. For instance, Twitter generates millions of packets of text. These statistics may be employed for commercial or charitable purposes. One of the hottest new buzzwords for many business strategies is the analysis of data from these social networking websites. Sentimental analysis can be used to manage election campaigns, global health problems, technical concepts, inventions, entertainment, and natural resource issues. Using Stanford NLP Libraries implemented in SaaS (cloud), which will manage all global current affairs, our proposed study assesses sentimental analysis of Twitter data. Implementing the cloud will improve speed to market, result growth, and process efficiency.n

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    Keywords: Sentimental analysis, natural language processing, Twitter4j, NLP, JSON

    n [if 424 equals=”Regular Issue”][This article belongs to International Journal of Computer Science Languages(ijcsl)]n

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    [/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue under section in International Journal of Computer Science Languages(ijcsl)][/if 424][if 424 equals=”Conference”]This article belongs to Conference [/if 424]

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    How to cite this article:n Rukmini Ankush Dhamdhere, Nikita Makarand Dhumal, Mayuri Keshav Gawali, Ganesh Pramod Kulkarni Sentimental Analysis in Twitter Using Python ijcsl July 6, 2023; 01:28-32

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    How to cite this URL: Rukmini Ankush Dhamdhere, Nikita Makarand Dhumal, Mayuri Keshav Gawali, Ganesh Pramod Kulkarni Sentimental Analysis in Twitter Using Python ijcsl July 6, 2023n {cited July 6, 2023};01:28-32. Available from: https://journals.stmjournals.com/ijcsl/article=July 6, 2023/view=0/

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    Volume 01
    Issue 01
    Received June 7, 2023
    Accepted June 23, 2023
    Published July 6, 2023

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