StackEmo-Towards Enhancing User Experience by Augmenting Stack Overflow with Emojis
This work addresses the need for visual sentiment cues to motivate users on Q&A platforms like Stack Overflow, though it is incremental as it applies existing sentiment analysis to a new domain.
The authors tackled the problem of missing sentiment representation on Stack Overflow by developing StackEmo, a Chrome plugin that augments comments with emojis based on sentiment analysis, and found that 83% of participants in a survey recommended it to peers.
With the increase in acceptance of open source platforms for knowledge sharing, Question and Answer (Q\&A) websites such as Stack Overflow have become increasingly popular in the programming domain. Many novice programmers visit Stack Overflow for reasons that include posing questions, finding answers for issues they come across in the process of programming. Practitioners voluntarily answer questions on Stack Overflow based on their experience or prior knowledge. Most of these answers are also accompanied by comments from users of Stack Overflow. Questions, answers and comments on Stack Overflow also include sentiments of users, which when analysed and presented could motivate users in reading and contributing to the posts. However, the sentiment of these posts is not being depicted in the current Stack Overflow platform. There is extensive research on analysing sentiments on social networking platforms such as twitter. Representing sentiment of a post might motivate users to follow or answer certain posts. While there exist several tools that augment or annotate Stack Overflow platform for developers, we are not aware of tools that deal with sentiment of the posts. In this paper, we propose StackEmo as a Google Chrome plugin to augment comments on Stack Overflow with emojis, based on the sentiment of the comments posted, with the aim to provide users with visual cues that could motivate the users to review and contribute to available comments. We evaluated StackEmo through an in-user likert scale based survey with 30 university students. The results of the survey provided us insights on improving StackEmo, with 83% participants having recommended the plugin to their peers.