Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM55105
Volume:
9 |
12 |
Dec 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This project develops a real-time Twitter sentiment analysis application using Streamlit, TF IDF vectorization, and Logistic Regression classification. Trained on the Sentiment140 dataset, the system preprocesses noisy social media text by removing URLs, mentions,hashtags, and normalizing casing/whitespace, then classifies tweets into positive, neutral, or negative categories with probability-based neutral threshold detection. The interactive web interface supports dual modes—manual text input and live
KEYWORDS
Publication Date
10/11/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
3
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...