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Identifying Political Sentiments on YouTube: A Systematic Comparison Regarding the Accuracy of Recurrent Neural Network and Machine Learning Models.

, , и . MISDOOM, том 12259 из Lecture Notes in Computer Science, стр. 107-121. Springer, (2020)

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Broadcasting one world: How watching online videos can elicit elevation and reduce stereotypes., , , , , и . New Media Soc., 19 (9): 1349-1368 (2017)Caught in a networked collusion? Homogeneity in conspiracy-related discussion networks on YouTube., , , и . Inf. Syst., (2022)Resource Usage in Online Courses: Analyzing Learner's Active and Passive Participation Patterns., , , , , , и . CSCL, International Society of the Learning Sciences, (2015)Another brick in the Facebook wall - How personality traits relate to the content of status updates., , , , , , , и . Comput. Hum. Behav., (2014)Einsatz einer mobilen Quiz-Applikation im Schulunterricht., , , , и . DeLFI, том P-207 из LNI, стр. 249-260. GI, (2012)Identifying Political Sentiments on YouTube: A Systematic Comparison Regarding the Accuracy of Recurrent Neural Network and Machine Learning Models., , и . MISDOOM, том 12259 из Lecture Notes in Computer Science, стр. 107-121. Springer, (2020)Investigating Incentives for Students to Provide Peer Feedback in a Semi-Open Online Course: An Experimental Study., , , и . OpenSym, стр. 19:1-19:7. ACM, (2014)