Do we like this, or do we like like this?” : Reflections on a Human-Centered Machine Learning Approach to Sentiment Analysis
Published in HCI International, 2023
Recommended citation: Sourojit Ghosh, Murtaza Ali, Anna Batra, Cheng Guo, Mohit Jain, Joseph Kang, Julia Kharchenko, Varun Suravajhela, Vincent Zhou, and Cecilia Aragon. (2023). “Do we like this, or do we like like this?” : Reflections on a Human-Centered Machine Learning Approach to Sentiment Analysis. In International Conference on Human-Computer Interaction, pp. 63-82. Cham: Springer Nature Switzerland, 2023.
Machine Learning is a powerful tool, but it also has a great potential to cause harm if not approached carefully. Designers must be reflexive and aware of their algorithms’ impacts, and one such way of reflection is known as human-centered machine learning. In this paper, we approach a classical problem that has been approached through ML - sentiment analysis - through a Human-Centered Machine Learning lens. Through a case study of trying to differentiate between degrees of positive emotions in reviews of online fanfiction, we offer a set of recommendations for future designers of ML-driven sentiment analysis algorithms.