Is Stack Overflow Overflowing With Questions and Tags
This addresses the issue of managing content overload on programming Q&A websites like Stack Overflow for developers and moderators, though it appears incremental as it builds on existing topic modeling methods.
The paper tackles the problem of manually analyzing questions and tags on Stack Overflow, which is time-consuming, by proposing a topic modeling technique to automatically discover themes, review question quality, and recommend appropriate tags to prevent unnecessary tag creation.
Programming question and answer (Q & A) websites, such as Quora, Stack Overflow, and Yahoo! Answer etc. helps us to understand the programming concepts easily and quickly in a way that has been tested and applied by many software developers. Stack Overflow is one of the most frequently used programming Q\&A website where the questions and answers posted are presently analyzed manually, which requires a huge amount of time and resource. To save the effort, we present a topic modeling based technique to analyze the words of the original texts to discover the themes that run through them. We also propose a method to automate the process of reviewing the quality of questions on Stack Overflow dataset in order to avoid ballooning the stack overflow with insignificant questions. The proposed method also recommends the appropriate tags for the new post, which averts the creation of unnecessary tags on Stack Overflow.