Real time Sentiment Analysis from Data Streaming

Samit Shivadekar, Ketan Shahapure, Shivam Vibhute and Milton Halem

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024, vol. 10, issue 1, 60-70

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.

Keywords: Twitter; Sentiment Analysis; Real-Time; Streaming Data; Topic Analysis; Model training; Prediction (search for similar items in EconPapers)
Date: 2024
Note: Article URL: https://ijsrcseit.com/CSEIT2390646
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v10:y2024:i1:id:hcseit2390646

DOI: 10.32628/CSEIT2390646

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