activity
20192026
most citedHow the world's collective attention is being paid to a pandemic: COVID-19 related n-gram time series for 24 languages on Twitter

63 citations · 240 across the 18 of their papers we have counts for

collaborators
Showing 2020Show all

8 papers · 1 filter

physics.soc-ph2020★ 2 cited

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…

physics.soc-ph2020★ 1 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-ph2020★ 14 cited

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…

physics.soc-ph2020★ 28 cited

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…

physics.soc-ph2020★ 4 cited

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…

physics.soc-ph2020★ 63 cited

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…

cs.CL2020★ 61 cited

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…

physics.soc-ph2020★ 20 cited

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…