63 citations · 270 across the 17 of their papers we have counts for
17 papers
A decomposition of book structure through ousiometric fluctuations in cumulative word-time
Mikaela Irene Fudolig, Thayer Alshaabi, Kathryn Cramer +2
While quantitative methods have been used to examine changes in word usage in books, studies have focused on overall trends, such as the shapes of narratives, which are independent…
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…
Quantifying language changes surrounding mental health on Twitter
Anne Marie Stupinski, Thayer Alshaabi, Michael V. Arnold +5
Mental health challenges are thought to afflict around 10% of the global population each year, with many going untreated due to stigma and limited access to services. Here, we expl…
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…
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…
Ratioing the President: An exploration of public engagement with Obama and Trump on Twitter
Joshua R. Minot, Michael V. Arnold, Thayer Alshaabi +2
The past decade has witnessed a marked increase in the use of social media by politicians, most notably exemplified by the 45th President of the United States (POTUS), Donald Trump…
The sociospatial factors of death: Analyzing effects of geospatially-distributed variables in a Bayesian mortality model for Hong Kong
Thayer Alshaabi, David Rushing Dewhurst, James P. Bagrow +2
Human mortality is in part a function of multiple socioeconomic factors that differ both spatially and temporally. Adjusting for other covariates, the human lifespan is positively…
Divergent modes of online collective attention to the COVID-19 pandemic are associated with future caseload variance
David Rushing Dewhurst, Thayer Alshaabi, Michael V. Arnold +3
Using a random 10% sample of tweets authored from 2019-09-01 through 2020-04-30, we analyze the dynamic behavior of words (1-grams) used on Twitter to describe the ongoing COVID-19…
The sleep loss insult of Spring Daylight Savings in the US is absorbed by Twitter users within 48 hours
Kelsey Linnell, Thayer Alshaabi, Thomas McAndrew +3
Sleep loss has been linked to heart disease, diabetes, cancer, and an increase in accidents, all of which are among the leading causes of death in the United States. Population-sca…
Hurricanes and hashtags: Characterizing online collective attention for natural disasters
Michael V. Arnold, David Rushing Dewhurst, Thayer Alshaabi +4
We study collective attention paid towards hurricanes through the lens of -grams on Twitter, a social media platform with global reach. Using hurricane name mentions as a proxy…
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…
The growing amplification of social media: Measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009-2020
Thayer Alshaabi, David R. Dewhurst, Joshua R. Minot +4
Working from a dataset of 118 billion messages running from the start of 2009 to the end of 2019, we identify and explore the relative daily use of over 150 languages on Twitter. W…
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…
The shocklet transform: A decomposition method for the identification of local, mechanism-driven dynamics in sociotechnical time series
David Rushing Dewhurst, Thayer Alshaabi, Dilan Kiley +4
We introduce a qualitative, shape-based, timescale-independent time-domain transform used to extract local dynamics from sociotechnical time series---termed the Discrete Shocklet T…