• Publications
  • Influence
Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter
TLDR
We construct a tunable, real-time, remote-sensing, and non-invasive, text-based hedonometer. Expand
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Measuring the Happiness of Large-Scale Written Expression: Songs, Blogs, and Presidents
TLDR
The importance of quantifying the nature and intensity of emotional states at the level of populations is evident: we would like to know how, when, and why individuals feel as they do if we wish to better construct public policy, build more successful organizations, and, from a scientific perspective, more fully understand economic and social phenomena. Expand
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Instagram photos reveal predictive markers of depression
TLDR
Using Instagram data from 166 individuals, we applied machine learning tools to successfully identify markers of depression. Expand
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The Geography of Happiness: Connecting Twitter Sentiment and Expression, Demographics, and Objective Characteristics of Place
TLDR
We conduct a detailed investigation of correlations between real-time expressions of individuals made across the United States and a wide range of emotional, geographic, demographic, and health characteristics. Expand
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Characterizing the Google Books Corpus: Strong Limits to Inferences of Socio-Cultural and Linguistic Evolution
TLDR
It is tempting to treat frequency trends from the Google Books data sets as indicators of the “true” popularity of various words and phrases. Expand
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An evolutionary algorithm approach to link prediction in dynamic social networks
TLDR
We provide an approach to predicting future links by applying the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) to optimize weights which are used in a linear combination of sixteen neighborhood and node similarity indices. Expand
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Forecasting the onset and course of mental illness with Twitter data
TLDR
We developed computational models to predict the emergence of depression and Post-Traumatic Stress Disorder in Twitter users. Expand
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Estimating and Correcting Global Weather Model Error
The purpose of the present study is to explore the feasibility of estimating and correcting systematic model errors using a simple and efficient procedure, inspired by papers by Leith as well asExpand
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Twitter reciprocal reply networks exhibit assortativity with respect to happiness
TLDR
We construct and examine the social network structure and dynamics of Twitter users over the time scales of days, weeks, and months. Expand
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Positivity of the English Language
TLDR
We show that the human-perceived positivity of over 10,000 of the most frequently used English words exhibits a clear positive bias. Expand
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