React is a popular JavaScript framework in modern web application development. Due to its high performance and efficiency, many developers use this framework. Although React library offers many advantages, it is not without its challenges. When using React library, developers often face problems where they often seek solutions through question-and-answer forums, such as Stack Overflow (SO). However, despite its high popularity, many React-related questions on SO remain unanswered. Thus, this study aims to analyze the factors associated with question answerability and difficulty levels of React-related questions on SO. To facilitate our study, Exploratory Data Analysis was applied to 534,820 questions, where they are filtered based on 23 React-related tags. We implemented a quantitative approach through text mining and statistical analysis. A logistic regression model was used to identify attributes associated with question answerability, while a simple linear regression model was employed to examine the correlation between user reputations and performance difficulty scores (PD Score). The results show that some attributes, such as number of views, code snippet inclusion, number of lines of code, and user reputation, positively affect the likelihood of question answerability. In contrast, the number of comments, question lengths, and presence of images in React-related questions reduce the probability of a question receiving responses from users. Further investigation indicates a negative correlation between user reputations and PD Score, where reputation increase corresponds to -0.092 reduction in PD score, signaling experienced users tend to propose more complex technical inquiries. This study provides insights into the characteristics of technical question-and-answer platforms, such as SO, that users need to consider the answerability factors when posting questions related to React.