Thread review sentimental analysis with tkinter GUI & tableau dashboard
<|reference_start|>Thread review sentimental analysis with tkinter GUI & tableau dashboard: This project focuses on utilizing a combination of Tkinter for GUI development and Tableauf for data visualization to do sentiment analysis on thread reviews.The main goal is to evaluate and visualize consumer sentiments as they are expressed in thread reviews in order to provide insights into areas for improvement, preferences, and customer satisfaction.The procedure starts with gathering thread reviews from many sources, which are then cleaned and prepared for analysis through preprocessing.Sentiment analysis classifies opinions as good, negative, or neutral based on the expressed sentiment by applying natural language processing techniques.The standard Python GUI package Tkinter is used to create an interactive user interface that allows users to enter thread reviews, start the sentiment analysis process, and see the analysis's outcomes.With the help of the user-friendly GUI, users may interact with the system and acquire insightful information with ease.Additionally, Tableau is used to produce a dynamic and eye-catching dashboard that displays the findings of the sentiment analysis using a variety of charts and graphs.Stakeholders may make educated decisions based on the studied data by using the dashboard, which provides a thorough overview of the sentiment distribution, frequency of positive and negative reviews, trending topics, and other pertinent indicators.Overall, this project offers a solid method for analyzing and comprehending customers' sentiments from thread reviews by integrating Tableauf for GUI development with Tkinter for sentiment analysis and data visualization. This allows for the creation of meaningful dashboards.<|reference_end|>
@article{donal2024thread,
    title={Thread review sentimental analysis with tkinter GUI & tableau dashboard},
    author={Robin Donal},
    journal={arXiv preprint arXiv:2405.00377},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.00377},
    primaryClass={cs.GT}
}