Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{173677,
        author = {Dhanashree B. Shinde and Ujjwal Anil Bodhe and Jayesh Ghanshyam Kamathe and Aman Mohammad Tuljapure and Arbaaz Bashir Khan},
        title = {SENTIMENT ANALYSIS FOR TEXT PROCESSING USING AI},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {1078-1080},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=173677},
        abstract = {Sentiment Analysis is a crucial component of Natural Language Processing (NLP), enabling computers to interpret and classify emotions within textual data. This paper presents a comprehensive AI-powered Sentiment Analysis system that processes and categorizes text as Positive, Negative, or Neutral using linguistic rule-based approaches and statistical models. The proposed system is designed for applications such as customer feedback analysis, social media monitoring, and product review classification. It integrates graphical user interface (GUI) support and real-time sentiment visualization to enhance usability. This research highlights the significance of sentiment analysis in automated decision-making and market trend forecasting.},
        keywords = {Sentiment Analysis, Data Pre-processing, Text Blob, Artificial Intelligence.},
        month = {March},
        }