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Real time Sentiment Analysis from Data Streaming

Author

Listed:
  • Samit Shivadekar
  • Ketan Shahapure
  • Shivam Vibhute
  • Milton Halem

Abstract

Public sentiment is a potent indicator of how people perceive and receive a topic. It has the power to make or break companies and people. Twitter is one of the best platforms in today’s generation to gauge public sentiment. [10] Utilizing the power and influence Twitter has we decided to create a service that would enable us to know how a trending topic is being viewed by the masses in real-time. The user gives the topic as input to the front-end graphical user interface that topic is then taken and fed to the Twitter streaming API. Tweets containing the hashtag of the topic mentioned by the user are returned and the sentiment of those tweets is predicted and sent to the front end where analysis prediction of the sentiment of the tweets is done dynamically as the tweets come in. By using our service for a few minutes the user will get to know what the overall outlook of a topic is and use that information as a guiding beacon for any future decisions regarding that topic.

Suggested Citation

  • Samit Shivadekar & Ketan Shahapure & Shivam Vibhute & Milton Halem, 2024. "Real time Sentiment Analysis from Data Streaming," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 10(1), pages 60-70, February.
    • Handle: RePEc:jbh:ijsrcs:v10:y2024:i1:id:hcseit2390646
    DOI: 10.32628/CSEIT2390646
    Note: Article URL: https://ijsrcseit.com/CSEIT2390646
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