Cover Image

Classification of Quality Characteristics in Online User Feedback using Linguistic Analysis, Crowdsourcing and LLMs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Groen, Eduard C., Dalpiaz, Fabiano, van Vliet, Martijn, Winter, Boris, Doerr, Joerg, Brinkkemper, Sjaak
Format:	Preprint
Published:	2025
Subjects:	Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Towards Crowd-Based Requirements Engineering for Digital Farming (CrowdRE4DF)
by: Groen, Eduard C., et al.
Published: (2024)

Text2Stories: Evaluating the Alignment Between Stakeholder Interviews and Generated User Stories
by: Dente, Francesco, et al.
Published: (2025)

RITA: A Tool for Automated Requirements Classification and Specification from Online User Feedback
by: Mallya, Manjeshwar Aniruddh, et al.
Published: (2026)

A Systematic Analysis of Higher Education on Software Engineering in the Netherlands
by: Heeren, Bastiaan, et al.
Published: (2025)

From Online User Feedback to Requirements: Evaluating Large Language Models for Classification and Specification Tasks
by: Mallya, Manjeshwar Aniruddh, et al.
Published: (2025)

Training LLMs for Generating IEC 61131-3 Structured Text with Online Feedback
by: Haag, Aaron, et al.
Published: (2024)

Replication in Requirements Engineering: the NLP for RE Case
by: Abualhaija, Sallam, et al.
Published: (2023)

Can User Feedback Help Issue Detection? An Empirical Study on a One-billion-user Online Service System
by: Jiang, Shuyao, et al.
Published: (2025)

A Dataset of Low-Rated Applications from the Amazon Appstore for User Feedback Analysis
by: Khan, Nek Dil, et al.
Published: (2026)

Can LLMs Generate User Stories and Assess Their Quality?
by: Quattrocchi, Giovanni, et al.
Published: (2025)

Enhancing User-Feedback Driven Requirements Prioritization
by: Chattopadhyay, Aurek, et al.
Published: (2026)

Unveiling Inclusiveness-Related User Feedback in Mobile Applications
by: Arony, Nowshin Nawar, et al.
Published: (2023)

Automating API Documentation from Crowdsourced Knowledge
by: Kou, Bonan, et al.
Published: (2026)

User Feedback in Continuous Software Engineering: Revealing the State-of-Practice
by: Tkalich, Anastasiia, et al.
Published: (2024)

Studying the Role of Reusing Crowdsourcing Knowledge in Software Development
by: Abdalkareem, Rabe
Published: (2025)

Towards Automated Crowdsourced Testing via Personified-LLM
by: Yu, Shengcheng, et al.
Published: (2026)

Hybrid LLM Routing for Efficient App Feedback Classification
by: Abedini, Yasaman, et al.
Published: (2025)

What Users Value and Critique: Large-Scale Analysis of User Feedback on AI-Powered Mobile Apps
by: Chhetri, Vinaik, et al.
Published: (2025)

May the Feedback Be with You! Unlocking the Power of Feedback-Driven Deep Learning Framework Fuzzing via LLMs
by: Yang, Shaoyu, et al.
Published: (2025)

A Survey on Feedback Types in Automated Programming Assessment Systems
by: Frankford, Eduard, et al.
Published: (2025)

Shannon Entropy is better Feature than Category and Sentiment in User Feedback Processing
by: Paredes, Andres Rojas, et al.
Published: (2024)

An Online Integrated Development Environment for Automated Programming Assessment Systems
by: Frankford, Eduard, et al.
Published: (2025)

A Systematic Literature Review on Task Recommendation Systems for Crowdsourced Software Engineering
by: Nirmani, Shashiwadana, et al.
Published: (2024)

Redefining Crowdsourced Test Report Prioritization: An Innovative Approach with Large Language Model
by: Ling, Yuchen, et al.
Published: (2024)

Leveraging LLMs for the Quality Assurance of Software Requirements
by: Lubos, Sebastian, et al.
Published: (2024)

On the Automated Processing of User Feedback
by: Maalej, Walid, et al.
Published: (2024)

Logging Like Humans for LLMs: Rethinking Logging via Execution and Runtime Feedback
by: Wang, Xin, et al.
Published: (2026)

Human-Aligned Enhancement of Programming Answers with LLMs Guided by User Feedback
by: Bappon, Suborno Deb, et al.
Published: (2026)

Helping LLMs Improve Code Generation Using Feedback from Testing and Static Analysis
by: Dolcetti, Greta, et al.
Published: (2024)

Understanding Feedback Mechanisms in Machine Learning Jupyter Notebooks
by: Shome, Arumoy, et al.
Published: (2024)

Designing an Objective-Driven Test Method for the Comparative Performance Evaluation of Commercial DTI Solutions for Counter UAS systems
by: Mohamoud, Ali, et al.
Published: (2024)

Breaking Single-Tester Limits: Multi-Agent LLMs for Multi-User Feature Testing
by: Feng, Sidong, et al.
Published: (2025)

Exploring LLMs Impact on Student-Created User Stories and Acceptance Testing in Software Development
by: Brockenbrough, Allan, et al.
Published: (2025)

A Benchmark Dataset And LLMs Comparison For NFR Classification With Explainable AI
by: Sakib, Esrat Ebtida, et al.
Published: (2025)

USeR: A Web-based User Story eReviewer for Assisted Quality Optimizations
by: Hallmann, Daniel, et al.
Published: (2025)

Crowdsourcing: A Framework for Usability Evaluation
by: Nasir, Muhammad
Published: (2024)

Screencast-Based Analysis of User-Perceived GUI Responsiveness
by: Liu, Wei, et al.
Published: (2025)

Quality Assurance of LLM-generated Code: Addressing Non-Functional Quality Characteristics
by: Sun, Xin, et al.
Published: (2025)

An Empirical Analysis of Mobile Energy Consumption Across User Configurations
by: Oliveira, Wellington
Published: (2026)

Identifying Concurrency Bug Reports via Linguistic Patterns
by: Shao, Shuai, et al.
Published: (2026)