  The wealth of information available through the Internet and social media is
unprecedented. Within computing fields, websites such as Stack Overflow are
considered important sources for users seeking solutions to their computing and
programming issues. However, like other social media platforms, Stack Overflow
contains a mixture of relevant and irrelevant information. In this paper, we
evaluated neural network models to predict the quality of questions on Stack
Overflow, as an example of Question Answering (QA) communities. Our results
demonstrate the effectiveness of neural network models compared to baseline
machine learning models, achieving an accuracy of 80%. Furthermore, our
findings indicate that the number of layers in the neural network model can
significantly impact its performance.
