18 results on '"Michael V Arnold"'
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2. Curating corpora with classifiers: A case study of clean energy sentiment online.
3. 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.
4. Sentiment and structure in word co-occurrence networks on Twitter.
5. Say Their Names: Resurgence in the collective attention toward Black victims of fatal police violence following the death of George Floyd.
6. Quantifying language changes surrounding mental health on Twitter.
7. Augmenting semantic lexicons using word embeddings and transfer learning.
8. Ratioing the President: An exploration of public engagement with Obama and Trump on Twitter.
9. Probability-turbulence divergence: A tunable allotaxonometric instrument for comparing heavy-tailed categorical distributions.
10. Computational timeline reconstruction of the stories surrounding Trump: Story turbulence, narrative control, and collective chronopathy.
11. Long-term word frequency dynamics derived from Twitter are corrupted: A bespoke approach to detecting and removing pathologies in ensembles of time series.
12. Hurricanes and hashtags: Characterizing online collective attention for natural disasters.
13. The growing echo chamber of social media: Measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009-2020.
14. How the world's collective attention is being paid to a pandemic: COVID-19 related 1-gram time series for 24 languages on Twitter.
15. Divergent modes of online collective attention to the COVID-19 pandemic are associated with future caseload variance.
16. Storywrangler: A massive exploratorium for sociolinguistic, cultural, socioeconomic, and political timelines using Twitter.
17. Fame and Ultrafame: Measuring and comparing daily levels of 'being talked about' for United States' presidents, their rivals, God, countries, and K-pop.
18. The shocklet transform: A decomposition method for the identification of local, mechanism-driven dynamics in sociotechnical time series.
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