HappyDB: A Corpus of 100,000 Crowdsourced Happy Moments
This provides a resource for researchers in NLP and positive psychology to study happiness expression, but it is incremental as it primarily introduces a new dataset.
The authors tackled the problem of understanding how people express happy moments in text by creating HappyDB, a publicly available corpus of 100,000 crowdsourced happy moments, and applied state-of-the-art NLP techniques to analyze it, showing the need for more advanced methods.
The science of happiness is an area of positive psychology concerned with understanding what behaviors make people happy in a sustainable fashion. Recently, there has been interest in developing technologies that help incorporate the findings of the science of happiness into users' daily lives by steering them towards behaviors that increase happiness. With the goal of building technology that can understand how people express their happy moments in text, we crowd-sourced HappyDB, a corpus of 100,000 happy moments that we make publicly available. This paper describes HappyDB and its properties, and outlines several important NLP problems that can be studied with the help of the corpus. We also apply several state-of-the-art analysis techniques to analyze HappyDB. Our results demonstrate the need for deeper NLP techniques to be developed which makes HappyDB an exciting resource for follow-on research.