most citedProbability-turbulence divergence: A tunable allotaxonometric instrument for comparing heavy-tailed categorical distributions

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CY2026

The triumphs and tragedies of fandom: Emotional arcs in NFL tweets

Elisabeth Kollrack, Michael V. Arnold, Peter Sheridan Dodds +1

Online fandom communities influence public opinion toward movies, musicians, and sports teams. Using a corpus of game-referencing tweets, we measure variation in sentiment toward N…

physics.soc-ph20261 cited

Probability-turbulence divergence: A tunable allotaxonometric instrument for comparing heavy-tailed categorical distributions

P. S. Dodds, J. R. Minot, M. V. Arnold +4

Real-world complex systems often comprise many distinct types of elements as well as many more types of networked interactions between elements. When the relative abundances of typ…

physics.soc-ph2026

Simon's model does not produce Zipf's law: The fundamental rich-get-richer mechanism for any power-law size ranking

Pablo Rosillo-Rodes, Julia Witte Zimmerman, Laurent Hébert-Dufresne +1

Many complex systems are composed of disparate, interacting types of varying sizes: Species abundances in ecosystems, firm sizes in markets, city populations in countries, word cou…

cs.SI2026

Crisis-induced differences in attention towards Ukraine in Twitter 2008-2023

Mark Mets, Peter Sheridan Dodds, Maximilian Schich

Aggression against Ukraine has drawn widespread international attention, particularly in the wake of the two Russian invasions into Ukrainian territory in 2014 and 2022. Although p…

cs.CL2025

Curating corpora with classifiers: A case study of clean energy sentiment online

Michael V. Arnold, Peter Sheridan Dodds, Christopher M. Danforth

Well curated, large-scale corpora of social media posts containing broad public opinion offer an alternative data source to complement traditional surveys. While surveys are effect…