HappyDB: A Corpus of 100,000 Crowdsourced Happy Moments

TL;DR

HappyDB is a large, publicly available corpus of 100,000 crowd-sourced happy moments, designed to facilitate NLP research into understanding and modeling expressions of happiness in text.

Contribution

The paper introduces HappyDB, a new extensive dataset of happy moments, and discusses its properties and potential for advancing NLP research in happiness expression.

Findings

Existing NLP techniques need to be improved for happiness analysis.

HappyDB reveals diverse ways people express happiness.

The corpus enables new research directions in positive psychology and NLP.

Abstract

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.