  Microblogging is a form of online communication by which users broadcast
brief text updates, also known as tweets, to the public or a selected circle of
contacts. A variegated mosaic of microblogging uses has emerged since the
launch of Twitter in 2006: daily chatter, conversation, information sharing,
and news commentary, among others. Regardless of their content and intended
use, tweets often convey pertinent information about their author's mood
status. As such, tweets can be regarded as temporally-authentic microscopic
instantiations of public mood state. In this article, we perform a sentiment
analysis of all public tweets broadcasted by Twitter users between August 1 and
December 20, 2008. For every day in the timeline, we extract six dimensions of
mood (tension, depression, anger, vigor, fatigue, confusion) using an extended
version of the Profile of Mood States (POMS), a well-established psychometric
instrument. We compare our results to fluctuations recorded by stock market and
crude oil price indices and major events in media and popular culture, such as
the U.S. Presidential Election of November 4, 2008 and Thanksgiving Day. We
find that events in the social, political, cultural and economic sphere do have
a significant, immediate and highly specific effect on the various dimensions
of public mood. We speculate that large scale analyses of mood can provide a
solid platform to model collective emotive trends in terms of their predictive
value with regards to existing social as well as economic indicators.
