학술논문

Can Sentiment Mining of Novice and Expert User Survey Feedback Enhance the Digital User Experience?
Document Type
Conference
Source
2022 8th International HCI and UX Conference in Indonesia (CHIuXiD) HCI and UX Conference in Indonesia (CHIuXiD), 2022 8th International. 1:19-24 Nov, 2022
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
General Topics for Engineers
Robotics and Control Systems
Human computer interaction
Sentiment analysis
Codes
Social networking (online)
User centered design
Collaboration
Prediction algorithms
cohort analysis
sentiment classification
user experience
machine learning
jupyter notebook
Language
Abstract
In recent years, sentiment mining has been used within politics and social media to understand the emotions and opinions that people have about society and different political groups to help bring change. However, in the user centered design process, a main component that helps bring change is the use of user feedback and there has been little research in terms of adopting sentiment mining to assist with this and the user experience of an application. This research paper implements the use of sentiment mining on user survey feedback from Jupyter Notebook and has identified different components of the user experience that caters for novice and expert users independently. Recommendations from this research will help Jupyter Notebook create a user experience that caters to novice and expert users and their workflow needs. This initial analysis has identified that sentiment mining provides important and subtle enhancements for user experience that other tools and techniques do not provide. Therefore, this is a worthwhile method of user experience assessment to foster to enhance a digital user experience.