2009/07/16 by Peter Sheridan Dodds, Christopher M. Danforth · 6 citations
Computer Science · Physics and Astronomy · Psychology · Social Sciences · #Computational and Text Analysis Methods #Mental Health via Writing #Sentiment Analysis and Opinion Mining #cs.SI #physics.soc-ph
paper · pdf · doi:10.1007/s10902-009-9150-9
published as Journal of Happiness Studies, 11(4), 441-456, 2010 (published online July 20, 2009) · 13 pages, 11 figures, 3 tables
openalex publication_date 2009/07/16 · openalex created_date 2016/06/24 · arxiv created 2017/03/06 · arxiv updated 2017/03/30 · openalex updated_date 2026/08/01
The importance of quantifying the nature and intensity of emotional states at the level of populations is evident: we would like to know how, when, and why individuals feel as they do if we wish, for example, to better construct public policy, build more successful organizations, and, from a scientific perspective, more fully understand economic and social phenomena. Here, by incorporating direct human assessment of words, we quantify happiness levels on a continuous scale for a diverse set of large-scale texts: song titles and lyrics, weblogs, and State of the Union addresses. Our method is transparent, improvable, capable of rapidly processing Web-scale texts, and moves beyond approaches based on coarse categorization. Among a number of observations, we find that the happiness of song lyrics trends downward from the 1960's to the mid 1990's while remaining stable within genres, and that the happiness of blogs has steadily increased from 2005 to 2009, exhibiting a striking rise and fall with blogger age and distance from the equator.