People's Emotions Analysis while Watching YouTube Videos
| Autor(en): | Motyka, Volodymyr Stepaniak, Yaroslav Nasalska, Mariia Vysotska, Victoria |
Herausgeber: | Cherednichenko, O. Universite Lumiere Lyon 2 UR ERIC � 5 avenue Mendes France Bron Cedex Chyrun, L. Ivan Franko National University of Lviv University Street 1 Lviv Vysotska, V. Lviv Polytechnic National University and, S. Bandera Street 12 Osnabruck University Friedrich-Janssen-Str. 1 Osnabruck |
Stichwörter: | Cluster analysis; correlation; Correlation methods; Data visualization; dislike; emotion; Emotion analysis; like; Number of views; sentiment analysis; smoothing; Smoothing methods; YouTube | Erscheinungsdatum: | 2023 | Herausgeber: | CEUR-WS | Journal: | CEUR Workshop Proceedings | Volumen: | 3403 | Startseite: | 500 – 525 | Zusammenfassung: | For analysis, a dataset containing information about videos from video hosting YouTube is selected, namely: title, video category, channel (author), number of views, number of likes, number of dislikes, date of video release. The purpose of the study was to analyze the state of people while watching videos on this platform. For this, various methods of visualization and data processing, smoothing methods, correlation and cluster analysis are used. © 2023 Copyright for this paper by its authors. |
Beschreibung: | Cited by: 0; Conference name: 7th International Conference on Computational Linguistics and Intelligent Systems. Volume III: Intelligent Systems Workshop, CoLInS 2023; Conference date: 20 April 2023 through 21 April 2023; Conference code: 188984 |
ISSN: | 1613-0073 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163088367&partnerID=40&md5=ead1545ba3875de17ba4402fbdcdf3b0 |
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