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Rukmini Ankush Dhamdhere, Nikita Makarand Dhumal, Mayuri Keshav Gawali, Ganesh Pramod Kulkarni
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- Student, Student, Student, Student,NBN Sinhgad School of Engineering, NBN Sinhgad School of Engineering, NBN Sinhgad School of Engineering, NBN Sinhgad School of Engineering,Maharashtra, Maharashtra, Maharashtra, Maharashtra,India, India, India, India
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Abstract
nSocial media websites are a great source of information because they have a lot of data. As an instance, Twitter generates millions of packets of data 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.
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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)]
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nRukmini 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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Full Text
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References
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| Volume | 01 |
| Issue | 01 |
| Received | June 7, 2023 |
| Accepted | June 23, 2023 |
| Published | July 6, 2023 |
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