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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 16 of 16 1 Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts Gallagher, Ryan J; Frank, Morgan R; Mitchell, Lewis... In: Springer Berlin Heidelberg (2021) BASE Show details 2 Storywrangler: A massive exploratorium for sociolinguistic, cultural, socioeconomic, and political timelines using Twitter Alshaabi, Thayer; Adams, Jane L.; Arnold, Michael V.... In: Sci Adv (2021) BASE Show details 3 How the world’s collective attention is being paid to a pandemic: COVID-19 related n-gram time series for 24 languages on Twitter Alshaabi, Thayer; Arnold, Michael V.; Minot, Joshua R.... In: PLoS One (2021) BASE Show details 4 Storywrangler: A massive exploratorium for sociolinguistic, cultural, socioeconomic, and political timelines using Twitter ... Alshaabi, Thayer; Adams, Jane L.; Arnold, Michael V.. - : arXiv, 2020 BASE Show details 5 Fame and Ultrafame: Measuring and comparing daily levels of `being talked about' for United States' presidents, their rivals, God, countries, and K-pop ... Dodds, Peter Sheridan; Minot, Joshua R.; Arnold, Michael V.. - : arXiv, 2019 BASE Show details 6 English verb regularization in books and tweets Gray, Tyler J.; Reagan, Andrew J.; Dodds, Peter Sheridan. - : Public Library of Science, 2018 BASE Show details 7 Sentiment analysis methods for understanding large-scale texts: a case for using continuum-scored words and word shift graphs [<Journal>] Reagan, Andrew J. [Verfasser]; Danforth, Christopher M. [Sonstige]; Tivnan, Brian [Sonstige]. DNB Subject Category Language Show details 8 Divergent discourse between protests and counter-protests: #BlackLivesMatter and #AllLivesMatter ... Gallagher, Ryan; Reagan, Andrew; Danforth, Christopher. - : SocArXiv, 2017 BASE Show details 9 Sentiment analysis methods for understanding large-scale texts: a case for using continuum-scored words and word shift graphs ... Reagan, Andrew; Danforth, Christopher; Tivnan, Brian. - : Figshare, 2017 BASE Show details 10 Sentiment analysis methods for understanding large-scale texts: a case for using continuum-scored words and word shift graphs ... Reagan, Andrew; Danforth, Christopher; Tivnan, Brian. - : Figshare, 2017 BASE Show details 11 Forecasting the onset and course of mental illness with Twitter data Reece, Andrew G.; Reagan, Andrew J.; Lix, Katharina L. M.. - : Nature Publishing Group UK, 2017 BASE Show details 12 The Lexicocalorimeter: Gauging public health through caloric input and output on social media Alajajian, Sharon E.; Williams, Jake Ryland; Reagan, Andrew J.; Alajajian, Stephen C.; Frank, Morgan R.; Mitchell, Lewis; Lahne, Jacob; Danforth, Christopher M.; Dodds, Peter Sheridan. - : Public Library of Science, 2017 Abstract: We propose and develop a Lexicocalorimeter: an online, interactive instrument for measuring the “caloric content” of social media and other large-scale texts. We do so by constructing extensive yet improvable tables of food and activity related phrases, and respectively assigning them with sourced estimates of caloric intake and expenditure. We show that for Twitter, our naive measures of “caloric input”, “caloric output”, and the ratio of these measures are all strong correlates with health and well-being measures for the contiguous United States. Our caloric balance measure in many cases outperforms both its constituent quantities; is tunable to specific health and well-being measures such as diabetes rates; has the capability of providing a real-time signal reflecting a population’s health; and has the potential to be used alongside traditional survey data in the development of public policy and collective self-awareness. Because our Lexicocalorimeter is a linear superposition of principled phrase scores, we also show we can move beyond correlations to explore what people talk about in collective detail, and assist in the understanding and explanation of how population-scale conditions vary, a capacity unavailable to black-box type methods. Keyword: Research Article URL: http://www.ncbi.nlm.nih.gov/pubmed/28187216 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5302853/ https://doi.org/10.1371/journal.pone.0168893 BASE Hide details 13 Forecasting the onset and course of mental illness with Twitter data Reece, Andrew G.; Reagan, Andrew J.; Lix, Katharina L. M.. - : Nature Publishing Group UK, 2017 BASE Show details 14 Forecasting the onset and course of mental illness with Twitter data ... Reece, Andrew G.; Reagan, Andrew J.; Lix, Katharina L. M.. - : arXiv, 2016 BASE Show details 15 The Lexicocalorimeter: Gauging public health through caloric input and output on social media Alajajian, Sharon E.; Williams, Jake Ryland; Reagan, Andrew J.... In: PLoS (2015) BASE Show details 16 Benchmarking sentiment analysis methods for large-scale texts: A case for using continuum-scored words and word shift graphs ... Reagan, Andrew J.; Tivnan, Brian; Williams, Jake Ryland. - : arXiv, 2015 BASE Show details

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