Is Stack Overflow Overflowing With Questions and Tags

TL;DR

This paper introduces a topic modeling approach to analyze Stack Overflow questions, aiming to identify themes, automate question quality review, and recommend relevant tags to improve content quality and organization.

Contribution

It presents a novel automated method for analyzing question themes, assessing question quality, and suggesting tags, reducing manual effort and improving Stack Overflow's content management.

Findings

Effective topic modeling of questions

Automated quality review of questions

Accurate tag recommendation system

Abstract

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.