Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter
Peter Sheridan Dodds,Kameron Decker Harris,Isabel M. Kloumann,Catherine A. Bliss,Christopher M. Danforth +4 more
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Examination of expressions made on the online, global microblog and social networking service Twitter is examined, uncovering and explaining temporal variations in happiness and information levels over timescales ranging from hours to years.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.read more
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References
More filters
Journal ArticleDOI
A mathematical theory of communication
TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
Journal ArticleDOI
Measurement of diversity
TL;DR: In this article, the authors define and examine a measure of concentration in terms of population constants, and examine the relationship between the characteristic and the index of diversity when both are applied to a logarithmic distribution.
Book
The Measurement of Meaning
TL;DR: In this article, the authors deal with the nature and theory of meaning and present a new, objective method for its measurement which they call the semantic differential, which can be adapted to a wide variety of problems in such areas as clinical psychology, social psychology, linguistics, mass communications, esthetics, and political science.
Proceedings ArticleDOI
What is Twitter, a social network or a news media?
TL;DR: In this paper, the authors have crawled the entire Twittersphere and found a non-power-law follower distribution, a short effective diameter, and low reciprocity, which all mark a deviation from known characteristics of human social networks.
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