Hot Topics and Common Challenges: an Empirical Study of React Discussions on Stack Overflow

2025-07-21

AI Summary

This study addresses the lack of clarity regarding pain points experienced by React developers in practice. Leveraging React-related question–answer data from Stack Overflow, we conduct a multi-dimensional empirical analysis. Methodologically, we integrate exploratory text mining, manual annotation of error types, and reputation-based stratified statistical analysis—first establishing associations among eight high-frequency keywords (e.g., *code*, *link*, *vir*), error category distributions, and user community status. Results reveal that algorithmic errors constitute the largest error category; notably, medium-reputation users contribute 55.77% of all questions, underscoring their role as a critical bottleneck cohort. The study uncovers the under-recognized needs of intermediate-level developers within the React ecosystem, offering a data-driven perspective to inform community support strategies and framework design improvements.

Technology Category

• Reasoning under Uncertainty: Uncertainty Representations
• Knowledge Representation and Reasoning: Computational Complexity of Reasoning
• Search and Optimization: Algorithm Configuration

Application Category

• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Web Mining and Content Analysis: Community question answering
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

React is a JavaScript library used to build user interfaces for single-page applications. Although recent studies have shown the popularity and advantages of React in web development, the specific challenges users face remain unknown. Thus, this study aims to analyse the React-related questions shared on Stack Overflow. The study utilizes an exploratory data analysis to investigate the most frequently discussed keywords, error classification, and user reputation-based errors, which is the novelty of this work. The results show the top eight most frequently used keywords on React-related questions, namely, code, link, vir, href, connect, azure, windows, and website. The error classification of questions from the sample shows that algorithmic error is the most frequent issue faced by all groups of users, where mid-reputation users contribute the most, accounting for 55.77%. This suggests the need for the community to provide guidance materials in solving algorithm-related problems. We expect that the results of this study will provide valuable insight into future research to support the React community during the early stages of implementation, facilitating their ability to effectively overcome challenges to adoption.

Problem

• Identify common React challenges on Stack Overflow
• Analyze error types and user reputation impact
• Provide insights to support React community adoption

Innovation

• Exploratory data analysis on Stack Overflow
• Keyword frequency and error classification
• User reputation-based error analysis