  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 use a real-time, remote-sensing,
non-invasive, text-based approach---a kind of 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 metric can be constructed and defended.
