Temporal patterns of happiness and information in a global social network: Hedonometrics and Twitter
📄 Original study ↗Plain English Summary
Ever wondered which day of the week is happiest? These researchers built a giant mood ring for the internet — a "hedonometer" measuring how happy people are based on the words they tweet. They rated over 10,000 English words on a happiness scale, then unleashed it on 46 billion words from 4.6 billion tweets. The results are delightful: Saturday is the happiest day, Tuesday the gloomiest, and people are cheeriest around 5-6 am — early birds really do get the emotional worm. Christmas tops the happiness charts while grim events drag the mood down. The really interesting twist? This tool later caught the eye of psi researchers, who used it to test whether collective Twitter sentiment might shift before big events — a kind of mass "gut feeling" in social media data.
Abstract
Individual happiness is a fundamental societal metric. Normally measured through self-report, happiness has often been indirectly characterized and overshadowed by more readily quantifiable economic indicators such as gross domestic product. Here, we examine expressions made on the online, global microblog and social networking service Twitter, uncovering and explaining temporal variations in happiness and information levels over timescales ranging from hours to years. Our data set comprises over 46 billion words contained in nearly 4.6 billion expressions posted over a 33 month span by over 63 million unique users. In measuring happiness, we construct a tunable, real-time, remote-sensing, and non-invasive, text-based hedonometer. In building our metric, made available with this paper, we conducted a survey to obtain happiness evaluations of over 10,000 individual words, representing a tenfold size improvement over similar existing word sets. Rather than being ad hoc, our word list is chosen solely by frequency of usage, and we show how a highly robust and tunable metric can be constructed and defended.
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📋 Cite this paper
Dodds, Peter Sheridan, Harris, Kameron Decker, Kloumann, Isabel M, Bliss, Catherine A, Danforth, Christopher M (2011). Temporal patterns of happiness and information in a global social network: Hedonometrics and Twitter. PLoS ONE. https://doi.org/10.1371/journal.pone.0026752
@article{dodds_2011_hedonometrics,
title = {Temporal patterns of happiness and information in a global social network: Hedonometrics and Twitter},
author = {Dodds, Peter Sheridan and Harris, Kameron Decker and Kloumann, Isabel M and Bliss, Catherine A and Danforth, Christopher M},
year = {2011},
journal = {PLoS ONE},
doi = {10.1371/journal.pone.0026752},
}