309 citations · 1.2k across the 28 of their papers we have counts for
29 papers
Ousiometrics: The essence of meaning aligns with a power-danger-structure framework instead of valence-arousal-dominance
P. S. Dodds, T. Alshaabi, M. I. Fudolig +7
From work emerging through the middle of the 20th century, the essence of meaning has become widely accepted as being described by the three orthogonal dimensions of valence, arous…
Long-term word frequency dynamics derived from Twitter are corrupted: A bespoke approach to detecting and removing pathologies in ensembles of time series
P. S. Dodds, J. R. Minot, M. V. Arnold +5
Maintaining the integrity of long-term data collection is an essential scientific practice. As a field evolves, so too will that field's measurement instruments and data storage sy…
Generalized Word Shift Graphs: A Method for Visualizing and Explaining Pairwise Comparisons Between Texts
Ryan J. Gallagher, Morgan R. Frank, Lewis Mitchell +4
A common task in computational text analyses is to quantify how two corpora differ according to a measurement like word frequency, sentiment, or information content. However, colla…
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…
Computational timeline reconstruction of the stories surrounding Trump: Story turbulence, narrative control, and collective chronopathy
P. S. Dodds, J. R. Minot, M. V. Arnold +4
Measuring the specific kind, temporal ordering, diversity, and turnover rate of stories surrounding any given subject is essential to developing a complete reckoning of that subjec…
Storywrangler: A massive exploratorium for sociolinguistic, cultural, socioeconomic, and political timelines using Twitter
Thayer Alshaabi, Jane L. Adams, Michael V. Arnold +5
In real-time, social media data strongly imprints world events, popular culture, and day-to-day conversations by millions of ordinary people at a scale that is scarcely conventiona…
How the world's collective attention is being paid to a pandemic: COVID-19 related n-gram time series for 24 languages on Twitter
T. Alshaabi, J. R. Minot, M. V. Arnold +6
In confronting the global spread of the coronavirus disease COVID-19 pandemic we must have coordinated medical, operational, and political responses. In all efforts, data is crucia…
Allotaxonometry and rank-turbulence divergence: A universal instrument for comparing complex systems
P. S. Dodds, J. R. Minot, M. V. Arnold +7
Complex systems often comprise many kinds of components which vary over many orders of magnitude in size: Populations of cities in countries, individual and corporate wealth in eco…
Fame and Ultrafame: Measuring and comparing daily levels of `being talked about' for United States' presidents, their rivals, God, countries, and K-pop
Peter Sheridan Dodds, Joshua R. Minot, Michael V. Arnold +5
When building a global brand of any kind -- a political actor, clothing style, or belief system -- developing widespread awareness is a primary goal. Short of knowing any of the st…
Social media usage patterns during natural hazards
Meredith T. Niles, Benjamin F. Emery, Andrew J. Reagan +2
Natural hazards are becoming increasingly expensive as climate change and development are exposing communities to greater risks. Preparation and recovery are critical for climate c…
English verb regularization in books and tweets
Tyler J. Gray, Andrew J. Reagan, Peter Sheridan Dodds +1
The English language has evolved dramatically throughout its lifespan, to the extent that a modern speaker of Old English would be incomprehensible without translation. One concret…
Towards a science of human stories: using sentiment analysis and emotional arcs to understand the building blocks of complex social systems
Andrew J. Reagan
Given the growing assortment of sentiment measuring instruments, it is imperative to understand which aspects of sentiment dictionaries contribute to both their classification accu…
Forecasting the onset and course of mental illness with Twitter data
Andrew G. Reece, Andrew J. Reagan, Katharina L. M. Lix +3
We developed computational models to predict the emergence of depression and Post-Traumatic Stress Disorder in Twitter users. Twitter data and details of depression history were co…
Public Opinion Polling with Twitter
Emily M. Cody, Andrew J. Reagan, Peter Sheridan Dodds +1
Solicited public opinion surveys reach a limited subpopulation of willing participants and are expensive to conduct, leading to poor time resolution and a restricted pool of expert…
Simon's fundamental rich-get-richer model entails a dominant first-mover advantage
Peter Sheridan Dodds, David Rushing Dewhurst, Fletcher F. Hazlehurst +5
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…
The emotional arcs of stories are dominated by six basic shapes
Andrew J. Reagan, Lewis Mitchell, Dilan Kiley +2
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. Ou…
Divergent discourse between protests and counter-protests: #BlackLivesMatter and #AllLivesMatter
Ryan J. Gallagher, Andrew J. Reagan, Christopher M. Danforth +1
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 ext…
Zipf's law is a consequence of coherent language production
Jake Ryland Williams, James P. Bagrow, Andrew J. Reagan +3
The task of text segmentation may be undertaken at many levels in text analysis---paragraphs, sentences, words, or even letters. Here, we focus on a relatively fine scale of segmen…
Benchmarking sentiment analysis methods for large-scale texts: A case for using continuum-scored words and word shift graphs
Andrew J. Reagan, Brian Tivnan, Jake Ryland Williams +2
The emergence and global adoption of social media has rendered possible the real-time estimation of population-scale sentiment, bearing profound implications for our understanding…
Predicting Flow Reversals in a Computational Fluid Dynamics Simulated Thermosyphon using Data Assimilation
Andrew J. Reagan, Yves Dubief, Peter Sheridan Dodds +1
A thermal convection loop is a annular chamber filled with water, heated on the bottom half and cooled on the top half. With sufficiently large forcing of heat, the direction of fl…
Tracking the Teletherms: The spatiotemporal dynamics of the hottest and coldest days of the year
Peter Sheridan Dodds, Lewis Mitchell, Andrew J. Reagan +1
Instabilities and long term shifts in seasons, whether induced by natural drivers or human activities, pose great disruptive threats to ecological, agricultural, and social systems…
The Lexicocalorimeter: Gauging public health through caloric input and output on social media
S. E. Alajajian, J. R. Williams, A. J. Reagan +6
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 construct…
The game story space of professional sports: Australian Rules Football
D. P. Kiley, A. J. Reagan, L. Mitchell +2
Sports are spontaneous generators of stories. Through skill and chance, the script of each game is dynamically written in real time by players acting out possible trajectories allo…
Reply to Garcia et al.: Common mistakes in measuring frequency dependent word characteristics
P. S. Dodds, E. M. Clark, S. Desu +11
We demonstrate that the concerns expressed by Garcia et al. are misplaced, due to (1) a misreading of our findings in [1]; (2) a widespread failure to examine and present words in…