activity
20142020
most citedInstagram photos reveal predictive markers of depression

34 citations · 106 across the 9 of their papers we have counts for

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Showing 2014Show all

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physics.soc-ph20141 cited

Constructing a taxonomy of fine-grained human movement and activity motifs through social media

Morgan R. Frank, Jake Ryland Williams, Lewis Mitchell +3

Profiting from the emergence of web-scale social data sets, numerous recent studies have systematically explored human mobility patterns over large populations and large time scale…

nlin.CD20143 cited

Computational Studies of Multiple-Particle Nonlinear Dynamics in a Spatio-Temporally periodic potential

Owen D. Myers, Junru Wu, Jeffrey S. Marshall +1

The spatio-temporally periodic (STP) potential is interesting in Physics due to the intimate coupling between its time and spatial components. In this paper we begin with a brief d…

cs.CL201434 cited

Text mixing shapes the anatomy of rank-frequency distributions: A modern Zipfian mechanics for natural language

Jake Ryland Williams, James P. Bagrow, Christopher M. Danforth +1

Natural languages are full of rules and exceptions. One of the most famous quantitative rules is Zipf's law which states that the frequency of occurrence of a word is approximately…

physics.soc-ph20143 cited

Human language reveals a universal positivity bias

Peter Sheridan Dodds, Eric M. Clark, Suma Desu +11

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…

cs.CL2014

Zipf's law holds for phrases, not words

Jake Ryland Williams, Paul R. Lessard, Suma Desu +4

With Zipf's law being originally and most famously observed for word frequency, it is surprisingly limited in its applicability to human language, holding over no more than three t…