Automated Social Media Feedback Analysis for Software Requirements Elicitation: A Case Study in the Streaming Industry

Melissa Silva, João Faria, João Faria

2025

Abstract

Requirements Engineering (RE) is crucial for product success but challenging for software with a broad user base, such as streaming platforms. Developers must analyze vast user feedback, but manual methods are impractical due to volume and diversity. This research addresses these challenges by automating the collection, filtering, summarization, and clustering of user feedback from social media, suggesting feature requests and bug fixes through an interactive platform. Data from Reddit, Twitter, iTunes, and Google Play is gathered via web crawlers and APIs and processed using a novel combination of natural language processing (NLP), machine learning (ML), large language models (LLMs), and incremental clustering. We evaluated our approach with a partner company in the streaming industry, extracting 66,168 posts related to 10 streaming services and identifying 22,847 as relevant with an ML classifier (75.5% precision, 74.2% recall). From the top 100 posts, a test user found 89 relevant and generated 47 issues in 80 minutes—a significant reduction in effort compared to a manual process. A usability study with six specialists yielded a SUS score of 83.33 (“Good”) and very positive feedback. The platform reduces cognitive overload by prioritizing high-impact posts and suggesting structured issue details, ensuring focus on insights while supporting scalability.

Paper Citation

in Harvard Style

Silva M. and Faria J. (2025). Automated Social Media Feedback Analysis for Software Requirements Elicitation: A Case Study in the Streaming Industry. In Proceedings of the 20th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE; ISBN 978-989-758-742-9, SciTePress, pages 149-160. DOI: 10.5220/0013364300003928

in Bibtex Style

@conference{enase25,
author={Melissa Silva and João Faria},
title={Automated Social Media Feedback Analysis for Software Requirements Elicitation: A Case Study in the Streaming Industry},
booktitle={Proceedings of the 20th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE},
year={2025},
pages={149-160},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013364300003928},
isbn={978-989-758-742-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE
TI - Automated Social Media Feedback Analysis for Software Requirements Elicitation: A Case Study in the Streaming Industry
SN - 978-989-758-742-9
AU - Silva M.
AU - Faria J.
PY - 2025
SP - 149
EP - 160
DO - 10.5220/0013364300003928
PB - SciTePress