StackEmo: Towards Enhancing User Experience by Augmenting Stack Overflow with Emojis
Fri 27 Aug 2021 00:20 - 00:25 - Analytics & Software Evolution—Recommender Systems Chair(s): Juri Di Rocco
Many novice programmers visit Stack Overflow for purposes that include posing questions and finding answers for issues they come across in the process of programming.
Many questions have more than one correct answer on Stack Overflow, which are accompanied by number of comments from the users. Comments help developers in identifying the answer that better fits their purpose. However, it is difficult to navigate through all the comments to select an answer. Adding relevant visual cues to comments could help developers in prioritizing the comments to be read. Comments logged generally include sentiments of users, which, when depicted visually, could motivate users in reading through the comments and also help them in prioritizing the comments. However, the sentiment of comments is not being explicitly depicted on the current Stack Overflow platform. While there exist many tools that augment or annotate Stack Overflow platform for developers, we are not aware of tools that annotate visual representations of sentiments to 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.
We evaluated StackEmo through an in-user likert scale based survey with 30 university students to understand user perception towards StackEmo. The results of the survey provided us insights on improving StackEmo, with 83% of the participants willing to recommend the plugin to their peers. The source code and tool are available for download on GitHub at: https://github.com/rishalab/StackEmo, and the demo can be found here on youtube: https://youtu.be/BCFlqvMhTMA.
Thu 26 AugDisplayed time zone: Athens change
12:00 - 13:00 | Analytics & Software Evolution—Recommender SystemsDemonstrations / Industry Papers / Research Papers +12h Chair(s): Phuong T. Nguyen University of L’Aquila, Gabriele Bavota Università della Svizzera italiana (USI) | ||
12:00 10mPaper | Which Abbreviations Should Be Expanded? Research Papers Yanjie Jiang Beijing Institute of Technology, Hui Liu Beijing Institute of Technology, Yuxia Zhang Beijing Institute of Technology, Nan Niu University of Cincinnati, Yuhai Zhao Northeastern University, Lu Zhang Peking University DOI | ||
12:10 5mPaper | BRAID: An API Recommender Supporting Implicit User Feedback Demonstrations Yu Zhou Nanjing University of Aeronautics and Astronautics, Haonan Jin Nanjing University of Aeronautics and Astronautics, Xinying Yang Nanjing University of Aeronautics and Astronautics, Taolue Chen University of London, Krishna Narasimhan TU Darmstadt, Harald Gall University of Zurich DOI | ||
12:15 5mPaper | Code2Que: A Tool for Improving Question Titles from Mined Code Snippets in Stack Overflow Demonstrations Zhipeng Gao Monash University, Xin Xia Huawei Technologies, David Lo Singapore Management University, John Grundy Monash University, Yuan-Fang Li Monash University DOI | ||
12:20 5mPaper | StackEmo: Towards Enhancing User Experience by Augmenting Stack Overflow with Emojis Demonstrations DOI Media Attached | ||
12:25 5mPaper | Domain Adaptation for an Automated Classification of Deontic Modalities in Software Engineering Contracts Industry Papers DOI | ||
12:30 30mLive Q&A | Q&A (Analytics & Software Evolution—Recommender Systems) Research Papers |
Fri 27 AugDisplayed time zone: Athens change
00:00 - 01:00 | Analytics & Software Evolution—Recommender SystemsDemonstrations / Research Papers / Industry Papers Chair(s): Juri Di Rocco University of L'Aquila | ||
00:00 10mPaper | Which Abbreviations Should Be Expanded? Research Papers Yanjie Jiang Beijing Institute of Technology, Hui Liu Beijing Institute of Technology, Yuxia Zhang Beijing Institute of Technology, Nan Niu University of Cincinnati, Yuhai Zhao Northeastern University, Lu Zhang Peking University DOI | ||
00:10 5mPaper | BRAID: An API Recommender Supporting Implicit User Feedback Demonstrations Yu Zhou Nanjing University of Aeronautics and Astronautics, Haonan Jin Nanjing University of Aeronautics and Astronautics, Xinying Yang Nanjing University of Aeronautics and Astronautics, Taolue Chen University of London, Krishna Narasimhan TU Darmstadt, Harald Gall University of Zurich DOI | ||
00:15 5mPaper | Code2Que: A Tool for Improving Question Titles from Mined Code Snippets in Stack Overflow Demonstrations Zhipeng Gao Monash University, Xin Xia Huawei Technologies, David Lo Singapore Management University, John Grundy Monash University, Yuan-Fang Li Monash University DOI | ||
00:20 5mPaper | StackEmo: Towards Enhancing User Experience by Augmenting Stack Overflow with Emojis Demonstrations DOI Media Attached | ||
00:25 5mPaper | Domain Adaptation for an Automated Classification of Deontic Modalities in Software Engineering Contracts Industry Papers DOI | ||
00:30 30mLive Q&A | Q&A (Analytics & Software Evolution—Recommender Systems) Research Papers |