Sentimental Analysis in Twitter Using Python

Year : 2023 | Volume :01 | Issue : 01 | Page : 28-32
By

Rukmini Ankush Dhamdhere

Nikita Makarand Dhumal

Mayuri Keshav Gawali

Ganesh Pramod Kulkarni

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

Abstract

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.

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

[This article belongs to International Journal of Computer Science Languages(ijcsl)]

How to cite this article: Rukmini Ankush Dhamdhere, Nikita Makarand Dhumal, Mayuri Keshav Gawali, Ganesh Pramod Kulkarni. Sentimental Analysis in Twitter Using Python. International Journal of Computer Science Languages. 2023; 01(01):28-32.
How to cite this URL: Rukmini Ankush Dhamdhere, Nikita Makarand Dhumal, Mayuri Keshav Gawali, Ganesh Pramod Kulkarni. Sentimental Analysis in Twitter Using Python. International Journal of Computer Science Languages. 2023; 01(01):28-32. Available from: https://journals.stmjournals.com/ijcsl/article=2023/view=114882


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Regular Issue Subscription Review Article
Volume 01
Issue 01
Received June 7, 2023
Accepted June 23, 2023
Published August 4, 2023
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