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{194368,
author = {Sakshi.P. Bachhav and Harshad.D. Kumavat and Suraj.M. Javdhav and Aniket.D.Shirsath and Mrs. V. B. Kale and Prof. M. P. Bhandakkar},
title = {Smart View – An AI -Powered Visualization, Reviewing & Recommendation App},
journal = {International Journal of Innovative Research in Technology},
year = {2026},
volume = {12},
number = {10},
pages = {4007-4012},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=194368},
abstract = {Smart View is an intelligent app review and sentiment analysis system designed to help users and organizations understand public opinion about mobile applications. The system allows users to enter an application name and automatically fetches real-time reviews from the Google Play Store using web scraping techniques. By converting large volumes of unstructured textual reviews into meaningful insights, SmartView supports better decision-making for developers, marketers, and end users. The proposed system is developed using Python with Flask as the backend framework, while HTML, CSS, and Bootstrap are used for building an interactive and user-friendly interface. Multiple machine learning algorithms such as Logistic Regression, Linear Support Vector Machine, and Naïve Bayes are employed, along with a deep learning-based Bidirectional LSTM model, to accurately classify user reviews into positive, negative, or average sentiments. This hybrid approach improves the accuracy and robustness of sentiment classification. SmartView presents the analysed results through a dashboard that includes average app ratings, sentiment distribution graphs, and sample positive and negative reviews. These visualizations make it easy to interpret user feedback at a glance. Overall, the system provides a scalable and efficient solution for real-time app review analysis, enabling developers to enhance app quality based on genuine user sentiment.},
keywords = {Sentiment Analysis, App Reviews, Machine Learning, Deep Learning, Bidirectional LSTM, Web Scraping, Python, Flask, Dashboard Visualization},
month = {March},
}
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