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The growing echo chamber of social media: Measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009-2020., , , , , , и . CoRR, (2020)Quantifying language changes surrounding mental health on Twitter., , , , , , , и . CoRR, (2021)Characterizing narrative time in books through fluctuations in power and danger arcs., , , , и . CoRR, (2022)Say Their Names: Resurgence in the collective attention toward Black victims of fatal police violence following the death of George Floyd., , , , , , , , , и . CoRR, (2021)The shocklet transform: a decomposition method for the identification of local, mechanism-driven dynamics in sociotechnical time series., , , , , , и . EPJ Data Sci., 9 (1): 3 (2020)Hurricanes and hashtags: Characterizing online collective attention for natural disasters., , , , , , и . CoRR, (2020)Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging., , , , , , , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 717-730. PMLR, (2022)Divergent modes of online collective attention to the COVID-19 pandemic are associated with future caseload variance., , , , , и . 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., , , , , , , , и . CoRR, (2020)Allotaxonometry and rank-turbulence divergence: a universal instrument for comparing complex systems., , , , , , , , , и . EPJ Data Sci., 12 (1): 37 (декабря 2023)