Image de couverture de livre

Beyond Keywords: A Context-based Hybrid Approach to Mining Ethical Concern-related App Reviews

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Sorathiya, Aakash, Ginde, Gouri
Format:	Preprint
Publié:	2024
Sujets:	Computation and Language Artificial Intelligence Software Engineering
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

CMER: A Context-Aware Approach for Mining Ethical Concern-related App Reviews
par: Sorathiya, Aakash, et autres
Publié: (2025)

Towards Extracting Ethical Concerns-related Software Requirements from App Reviews
par: Sorathiya, Aakash, et autres
Publié: (2024)

Exploring Ethical Concerns of Mobile Applications from App Reviews: A Literature Survey
par: Sorathiya, Aakash, et autres
Publié: (2026)

SAGE: A Context-Aware Approach for Mining Privacy Requirements Relevant Reviews from Mental Health Apps
par: Sorathiya, Aakash, et autres
Publié: (2025)

Towards Extracting Software Requirements from App Reviews using Seq2seq Framework
par: Sorathiya, Aakash, et autres
Publié: (2025)

Ethical software requirements from user reviews: A systematic literature review
par: Sorathiya, Aakash, et autres
Publié: (2024)

Can We Enhance Bug Report Quality Using LLMs?: An Empirical Study of LLM-Based Bug Report Generation
par: Acharya, Jagrit, et autres
Publié: (2025)

"So what if I used GenAI?" -- Implications of Using Cloud-based GenAI in Software Engineering Research
par: Ginde, Gouri
Publié: (2024)

What Software Engineering Looks Like to AI Agents? -- An Empirical Study of AI-Only Technical Discourse on MoltBook
par: Huo, Junyu, et autres
Publié: (2026)

Fairness Concerns in App Reviews: A Study on AI-based Mobile Apps
par: Nasab, Ali Rezaei, et autres
Publié: (2024)

Empirical Analysis and Detection of Hallucinations in LLM-Generated Bug Report Summaries
par: Nirujan, Hinduja, et autres
Publié: (2026)

Self-Explained Keywords Empower Large Language Models for Code Generation
par: Fan, Lishui, et autres
Publié: (2024)

A Case Study of Web App Coding with OpenAI Reasoning Models
par: Cui, Yi
Publié: (2024)

BugsRepo: A Comprehensive Curated Dataset of Bug Reports, Comments and Contributors Information from Bugzilla
par: Acharya, Jagrit, et autres
Publié: (2025)

Automatic Classification of User Requirements from Online Feedback -- A Replication Study
par: Bhatt, Meet, et autres
Publié: (2025)

Attention Mechanism and Heuristic Approach: Context-Aware File Ranking Using Multi-Head Self-Attention
par: Sharma, Pradeep Kumar, et autres
Publié: (2026)

Zero-shot Bilingual App Reviews Mining with Large Language Models
par: Wei, Jialiang, et autres
Publié: (2023)

A Study of In-Context-Learning-Based Text-to-SQL Errors
par: Shen, Jiawei, et autres
Publié: (2025)

Towards an Understanding of Context Utilization in Code Intelligence
par: Wang, Yanlin, et autres
Publié: (2025)

Scaling Granite Code Models to 128K Context
par: Stallone, Matt, et autres
Publié: (2024)

McMining: Automated Discovery of Misconceptions in Student Code
par: Al-Hossami, Erfan, et autres
Publié: (2025)

The Best Ends by the Best Means: Ethical Concerns in App Reviews
par: Olson, Lauren, et autres
Publié: (2024)

AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents
par: Trivedi, Harsh, et autres
Publié: (2024)

MOSS: Enabling Code-Driven Evolution and Context Management for AI Agents
par: Zhu, Ming, et autres
Publié: (2024)

COMET: Generating Commit Messages using Delta Graph Context Representation
par: Mandli, Abhinav Reddy, et autres
Publié: (2024)

YABLoCo: Yet Another Benchmark for Long Context Code Generation
par: Valeev, Aidar, et autres
Publié: (2025)

APEX-SWE
par: Kottamasu, Abhi, et autres
Publié: (2026)

Advancing Language Models for Code-related Tasks
par: Tian, Zhao
Publié: (2026)

JumpCoder: Go Beyond Autoregressive Coder via Online Modification
par: Chen, Mouxiang, et autres
Publié: (2024)

Stingy Context: 18:1 Hierarchical Code Compression for LLM Auto-Coding
par: Ostby, David Linus
Publié: (2026)

Code Sharing In Prediction Model Research: A Scoping Review
par: Sounack, Thomas, et autres
Publié: (2026)

Beyond Correctness: Benchmarking Multi-dimensional Code Generation for Large Language Models
par: Zheng, Jiasheng, et autres
Publié: (2024)

Demo-Craft: Using In-Context Learning to Improve Code Generation in Large Language Models
par: Kapu, Nirmal Joshua, et autres
Publié: (2024)

Is Open Source the Future of AI? A Data-Driven Approach
par: Vake, Domen, et autres
Publié: (2025)

CodeNav: Beyond tool-use to using real-world codebases with LLM agents
par: Gupta, Tanmay, et autres
Publié: (2024)

A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond
par: Sun, Qiushi, et autres
Publié: (2024)

SecureReviewer: Enhancing Large Language Models for Secure Code Review through Secure-aware Fine-tuning
par: Liu, Fang, et autres
Publié: (2025)

Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context Learning
par: Jin, Hongwei, et autres
Publié: (2024)

CodeEvo: Interaction-Driven Synthesis of Code-centric Data through Hybrid and Iterative Feedback
par: Sun, Qiushi, et autres
Publié: (2025)

A Review of Prominent Paradigms for LLM-Based Agents: Tool Use (Including RAG), Planning, and Feedback Learning
par: Li, Xinzhe
Publié: (2024)