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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 – 9 of 9 1 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 2 The Lexicocalorimeter: Gauging public health through caloric input and output on social media Alajajian, Sharon E.; Williams, Jake Ryland; Reagan, Andrew J.. - : Public Library of Science, 2017 BASE Show details 3 Boundary-based MWE segmentation with text partitioning ... Williams, Jake Ryland. - : arXiv, 2016 BASE Show details 4 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 5 Sifting Robotic from Organic Text: A Natural Language Approach for Detecting Automation on Twitter ... Clark, Eric M.; Williams, Jake Ryland; Jones, Chris A.. - : arXiv, 2015 BASE Show details 6 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 7 Identifying missing dictionary entries with frequency-conserving context models ... Williams, Jake Ryland; Clark, Eric M.; Bagrow, James P.. - : arXiv, 2015 BASE Show details 8 Vaporous Marketing: Uncovering Pervasive Electronic Cigarette Advertisements on Twitter ... Clark, Eric M.; Jones, Chris A.; Williams, Jake Ryland; Kurti, Allison N.; Nortotsky, Michell Craig; Danforth, Christopher M.; Dodds, Peter Sheridan. - : arXiv, 2015 Abstract: Background: Twitter has become the "wild-west" of marketing and promotional strategies for advertisement agencies. Electronic cigarettes have been heavily marketed across Twitter feeds, offering discounts, "kid-friendly" flavors, algorithmically generated false testimonials, and free samples. Methods:All electronic cigarette keyword related tweets from a 10% sample of Twitter spanning January 2012 through December 2014 (approximately 850,000 total tweets) were identified and categorized as Automated or Organic by combining a keyword classification and a machine trained Human Detection algorithm. A sentiment analysis using Hedonometrics was performed on Organic tweets to quantify the change in consumer sentiments over time. Commercialized tweets were topically categorized with key phrasal pattern matching. Results:The overwhelming majority (80%) of tweets were classified as automated or promotional in nature. The majority of these tweets were coded as commercialized (83.65% in 2013), up to 33% of which ... Keyword: FOS Computer and information sciences; Social and Information Networks cs.SI URL: https://arxiv.org/abs/1508.01843 https://dx.doi.org/10.48550/arxiv.1508.01843 BASE Hide details 9 Text mixing shapes the anatomy of rank-frequency distributions: A modern Zipfian mechanics for natural language ... Williams, Jake Ryland; Bagrow, James P.; Danforth, Christopher M.. - : arXiv, 2014 BASE Show details

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