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Sifting robotic from organic text: A natural language approach for detecting automation on Twitter.

, , , , , and . J. Comput. Sci., (2016)

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Identifying missing dictionary entries with frequency-conserving context models., , , , and . CoRR, (2015)Which Tweets 'Deserve' to be Included in News Stories? Chronemics of Tweet Embedding., , and . HICSS, page 5983-5993. ScholarSpace, (2023)Human language reveals a universal positivity bias, , , , , , , , , and 4 other author(s). Proceedings of the National Academy of Sciences, (2015)Explicit Foundation Model Optimization with Self-Attentive Feed-Forward Neural Units., and . CoRR, (2023)The Earth Is Flat and the Sun Is Not a Star: The Susceptibility of GPT-2 to Universal Adversarial Triggers., and . AIES, page 566-573. ACM, (2021)BuzzFace: A News Veracity Dataset with Facebook User Commentary and Egos., and . ICWSM, page 531-540. AAAI Press, (2018)TAMICA: Tailorable Autonomous Motivational Interviewing Conversational Agent., , , , , , and . PervasiveHealth, page 411-414. ACM, (2020)Detecting Social Bots on Facebook in an Information Veracity Context., , and . ICWSM, page 463-472. AAAI Press, (2019)Sifting robotic from organic text: A natural language approach for detecting automation on Twitter., , , , , and . J. Comput. Sci., (2016)Text mixing shapes the anatomy of rank-frequency distributions: A modern Zipfian mechanics for natural language., , , and . CoRR, (2014)