Abstract: The overwhelming volume of unfiltered and potentially harmful content on social media and websites poses significant challenges to digital well-being, especially for users seeking a more controlled and distraction-free online experience. In response to this issue, this study presents the design, development, and evaluation of SocialScreen: a Chromium browser extension that filters social media posts and web text content using a Fuzzy Matching algorithm. The primary objective of the project is to provide users with an effective tool for managing online content by allowing both preset and user-defined datasets for filtering. The extension was developed using Visual Studio Code, JavaScript, Node.js, Webpack, HTML, and CSS, and was guided by the Agile methodology throughout the software development lifecycle. Functional and performance testing were conducted to ensure the reliability, efficiency, and responsiveness of the system. Evaluation sessions and structured surveys gathered feedback from both end-users and IT professionals, focusing on usability and software quality, based on ISO/IEC 25010 standards.
Results indicate that SocialScreen demonstrated strong performance in maintainability, with a modular design and ease of updates, supported by comprehensive documentation. However, some limitations were identified in the area of portability, particularly with respect to accessibility compliance and full compatibility across all Chromium-based browsers. The implementation of the Fuzzy Matching algorithm proved to be a valuable enhancement, enabling flexible and accurate filtering of textual content. The Agile methodology facilitated iterative improvements, ensuring a user-centric development approach. Overall, evaluation findings confirmed the tool’s functional effectiveness and acceptable quality performance.
Keywords: Chromium Plugin, Fuzzy Matching Algorithm, Content Filtering, Social Media, JavaScript.
Title: SocialScreen: A Chromium Plugin That Filters Social Media Posts And Web Text Content Using Fuzzy Matching
Author: Roumel John S. Nidoy, Jonh Zaldy Catalan, Anthony Ross D. Arayata, Elmer C. Matel, Elizabeth S. Nsubuga, Jerian R. Peren
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
Vol. 13, Issue 2, April 2025 - June 2025
Page No: 80-91
Research Publish Journals
Website: www.researchpublish.com
Published Date: 30-June-2025
