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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TLDR
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
Citations
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Journal ArticleDOI
Positivity of the English language.
Isabel M. Kloumann,Christopher M. Danforth,Kameron Decker Harris,Catherine A. Bliss,Peter Sheridan Dodds +4 more
TL;DR: It is reported that the human-perceived positivity of over 10,000 of the most frequently used English words exhibits a clear positive bias.
Posted Content
Twitter reciprocal reply networks exhibit assortativity with respect to happiness
Catherine A. Bliss,Isabel M. Kloumann,Kameron Decker Harris,Christopher M. Danforth,Peter Sheridan Dodds +4 more
TL;DR: In this paper, the authors employed hedonometric analysis methods to investigate patterns of sentiment expression and found that users' average happiness scores were positively and significantly correlated with those of users one, two, and three links away.
Proceedings ArticleDOI
Best-Worst Scaling More Reliable than Rating Scales: A Case Study on Sentiment Intensity Annotation
TL;DR: This work sets up an experiment that directly compares the rating scale method with Best–worst scaling and shows that with the same total number of annotations, BWS produces significantly more reliable results than the rating Scale.
Posted Content
Survey of Computational Approaches to Lexical Semantic Change
TL;DR: This article focuses on diachronic conceptual change as an extension of semantic change, and a survey of recent computational techniques to tackle lexical semantic change currently under review.
Proceedings ArticleDOI
SemEval-2016 Task 7: Determining Sentiment Intensity of English and Arabic Phrases
TL;DR: A shared task on automatically determining sentiment intensity of a word or a phrase as well as phrases formed by words with opposing polarities, taken from general English, English Twitter, and Arabic Twitter.
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