Joshua R. Minot
According to our database1,
Joshua R. Minot
authored at least 20 papers
between 2019 and 2023.
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Bibliography
2023
Allotaxonometry and rank-turbulence divergence: a universal instrument for comparing complex systems.
EPJ Data Sci., December, 2023
2022
Interpretable Bias Mitigation for Textual Data: Reducing Genderization in Patient Notes While Maintaining Classification Performance.
ACM Trans. Comput. Heal., 2022
2021
The growing amplification of social media: measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009-2020.
EPJ Data Sci., 2021
Ousiometrics and Telegnomics: The essence of meaning conforms to a two-dimensional powerful-weak and dangerous-safe framework with diverse corpora presenting a safety bias.
CoRR, 2021
Say Their Names: Resurgence in the collective attention toward Black victims of fatal police violence following the death of George Floyd.
CoRR, 2021
The incel lexicon: Deciphering the emergent cryptolect of a global misogynistic community.
CoRR, 2021
Interpretable bias mitigation for textual data: Reducing gender bias in patient notes while maintaining classification performance.
CoRR, 2021
2020
The shocklet transform: a decomposition method for the identification of local, mechanism-driven dynamics in sociotechnical time series.
EPJ Data Sci., 2020
Probability-turbulence divergence: A tunable allotaxonometric instrument for comparing heavy-tailed categorical distributions.
CoRR, 2020
Long-term word frequency dynamics derived from Twitter are corrupted: A bespoke approach to detecting and removing pathologies in ensembles of time series.
CoRR, 2020
Computational timeline reconstruction of the stories surrounding Trump: Story turbulence, narrative control, and collective chronopathy.
CoRR, 2020
Storywrangler: A massive exploratorium for sociolinguistic, cultural, socioeconomic, and political timelines using Twitter.
CoRR, 2020
Ratioing the President: An exploration of public engagement with Obama and Trump on Twitter.
CoRR, 2020
Divergent modes of online collective attention to the COVID-19 pandemic are associated with future caseload variance.
CoRR, 2020
Hurricanes and hashtags: Characterizing online collective attention for natural disasters.
CoRR, 2020
How the world's collective attention is being paid to a pandemic: COVID-19 related 1-gram time series for 24 languages on Twitter.
CoRR, 2020
The growing echo chamber of social media: Measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009-2020.
CoRR, 2020
2019
Fame and Ultrafame: Measuring and comparing daily levels of 'being talked about' for United States' presidents, their rivals, God, countries, and K-pop.
CoRR, 2019