Amazon HappyDB
HackerEarth_Machine_Learning_Intern_Test
HappyDB is a corpus of more than 100,000 happy moments crowd-sourced via Amazon’s Mechanical Turk.
Each worker is given the following task: What made you happy today? Reflect on the past 24 hours, and recall three actual events that happened to you that made you happy. Write down your happy moment in a complete sentence. (Write three such moments.)
The goal of the corpus is to advance the understanding of the causes of happiness through text-based reflection.
Based on the happy moment statement you have to predict the category of happiness, i.e. the source of happiness which is typically either of the following: 'bonding', 'achievement', 'affection', 'leisure', 'enjoy_the_moment', 'nature', 'exercise'.
##Data This research dives into a handy dataset that can help shed some light on the fundamentals of happiness. HappyDB is a set of 100,000+ happy experiences gathered through Amazon Mechanical Turk from March to June of 2017. It contains the experiences and demographics from tens of thousands of contributors around the world. Interestingly, some basic text analysis methods can help us learn a lot from this data.
Reference
Akari Asai, Sara Evensen, Behzad Golshan, Alon Halevy, Vivian Li, Andrei Lopatenko, Daniela Stepanov, Yoshihiko Suhara, Wang-Chiew Tan, Yinzhan Xu, ``HappyDB: A Corpus of 100,000 Crowdsourced Happy Moments'', LREC '18, May 2018. (to appear)