most citedLong-term word frequency dynamics derived from Twitter are corrupted: A bespoke approach to detecting and removing pathologies in ensembles of time series

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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

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

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…

physics.soc-ph2020

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…