HappyDB: A Corpus of 100,000 Crowdsourced Happy Moments Part of the work was done while Asai, Evensen, and Xu were at Recruit Institute of Technology.
Table 5: Average LIWC Scores for (cleaned) HappyDB compared to those of other text corpora of expressive writing, novels, and blogs [Pennebaker et al.2015a]. All three categories provide scores in the range from 1 to 99.
['[BOLD] LIWC  [BOLD] Category', '[BOLD] HappyDB', '[BOLD] Expressive', '[BOLD] Novels', '[BOLD] Blogs']
These categories are defined as follows: analytic refers to a measurement of the author’s logical thinking, as opposed to narrative and informal thinking; authentic approximates how honest and disclosing the writing is; and tone measures how positive or negative the text is. As expected, HappyDB has a higher score for tone than any of the other corpora analyzed. More interestingly, the analytic score for HappyDB is quite high and very close to that of Novels, yet the authentic score (also quite high) is closer to that for Expressive Writing. Our analysis of LIWC scores suggest that our corpus is very disclosing and honest which makes it an ideal corpus for studying emotions expressed in text.