Andrew J. Reagan

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Using human evaluation of 100,000 words spread across 24 corpora in 10 languages diverse in origin and culture, we present evidence of a deep imprint of human sociality in language, observing that (i) the words of natural human language possess a universal positivity bias, (ii) the estimated emotional content of words is consistent between languages under(More)
Advances in computing power, natural language processing, and digitization of text now make it possible to study a culture’s evolution through its texts using a ‘big data’ lens. Our ability to communicate relies in part upon a shared emotional experience, with stories often following distinct emotional trajectories and forming patterns that are meaningful(More)
Andrew Reagan, 2 Brian Tivnan, 3 Jake Ryland Williams, Christopher M. Danforth, 2 and Peter Sheridan Dodds 2 Department of Mathematics & Statistics, Computational Story Lab, & the Vermont Advanced Computing Core, University of Vermont, Burlington, VT, 05405 Vermont Complex Systems Center, University of Vermont, Burlington, VT, 05405 The MITRE Corporation,(More)
Since the shooting of Black teenager Michael Brown by White police officer Darren Wilson in Ferguson, Missouri, the protest hashtag #BlackLivesMatter has amplified critiques of extrajudicial killings of Black Americans. In response to #BlackLivesMatter, other Twitter users have adopted #AllLivesMatter, a counter-protest hashtag whose content argues that(More)
The consequences of anthropogenic climate change are extensively debated through scientific papers, newspaper articles, and blogs. Newspaper articles may lack accuracy, while the severity of findings in scientific papers may be too opaque for the public to understand. Social media, however, is a forum where individuals of diverse backgrounds can share their(More)
Complex, dynamic networks underlie many systems, and understanding these networks is the concern of a great span of important scientific and engineering problems. Quantitative description is crucial for this understanding yet, due to a range of measurement problems, many real network datasets are incomplete. Here we explore how accidentally missing or(More)
We propose and develop a Lexicocalorimeter: an online, interactive instrument for measuring the "caloric content" of social media and other large-scale texts. We do so by constructing extensive yet improvable tables of food and activity related phrases, and respectively assigning them with sourced estimates of caloric intake and expenditure. We show that(More)
Peter Sheridan Dodds, 2, ∗ Eric M. Clark, 2 Suma Desu, Morgan R. Frank, Andrew J. Reagan, 2 Jake Ryland Williams, 2 Lewis Mitchell, Kameron Decker Harris, Isabel M. Kloumann, James P. Bagrow, 2 Karine Megerdoomian, Matthew T. McMahon, Brian F. Tivnan, 2, † and Christopher M. Danforth 2, ‡ Computational Story Lab, Vermont Advanced Computing Core, & the(More)
Jake Ryland Williams, ∗ James P. Bagrow, † Andrew J. Reagan, ‡ Sharon E. Alajajian, § Christopher M. Danforth, ¶ and Peter Sheridan Dodds ∗∗ School of Information, University of California, Berkeley 102 South Hall #4600 Berkeley, CA 94720-4600. Department of Mathematics & Statistics, Vermont Complex Systems Center, Computational Story Lab, & the Vermont(More)
Herbert Simon's classic rich-get-richer model is one of the simplest empirically supported mechanisms capable of generating heavy-tail size distributions for complex systems. Simon argued analytically that a population of flavored elements growing by either adding a novel element or randomly replicating an existing one would afford a distribution of group(More)