7 citations · 17 across the 4 of their papers we have counts for
6 papers
Say Their Names: Resurgence in the collective attention toward Black victims of fatal police violence following the death of George Floyd
Henry H. Wu, Ryan J. Gallagher, Thayer Alshaabi +7
The murder of George Floyd by police in May 2020 sparked international protests and renewed attention in the Black Lives Matter movement. Here, we characterize ways in which the on…
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…
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…
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…