īendimerad A, Plantevit M, Robardet C, Amer-Yahia S (2019) User-driven geolocated event detection in social media. In: 2020 5th International Conference on Informatics and Computing, ICIC 2020.
#TRENDING YOUTUBE TAGS MOVIE#
Īlkaff M, Rizky Baskara A, Hendro Wicaksono Y (2020) Sentiment analysis of indonesian movie trailer on YouTube using delta TF-IDF and SVM.
Lecture Notes Comput Sci (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 11549(LNCS):224–233. Īlassad M, Agarwal N, Hussain MN (2019) Examining intensive groups in youtube commenter networks. In: HT 2014-Proceedings of the 25th ACM conference on hypertext and social media. Īgarwal S, Sureka A (2014) A focused crawler for mining hate and extremism promoting videos on YouTube. The results reveal the tendency of United States YouTube users in terms of video tag popularity.Ībebe MA, Tekli J, Getahun F, Chbeir R, Tekli G (2020) Generic metadata representation framework for social-based event detection, description, and linkage. The experimental results show the effectiveness of the proposed algorithm on discovering popular and persistent tags. The proposed algorithm is experimentally evaluated on the dataset. A new algorithm is proposed, named as Popular and Persistent Tag Discovery algorithm (PPTagD algorithm), which uses proposed method. In this study, a new method is proposed for popular and persistent tags discovery which uses YouTube trending video dataset of United States for the year of 2021. In the literature, several studies are performed for sentiment analysis of YouTube video comments, video recommendation methods, and trending video analyses approaches. However, YouTube big data analysis has several challenges, such as video content issues, textual and semantic challenges, different metadata information about videos, and big data nature of YouTube datasets. Analyzing YouTube big datasets is essential for discovering user-video relations, video recommendation, semantic analysis of video comments and trending videos analysis. Based on these advantages, YouTube datasets have a big data nature in terms of data analytics. YouTube is the most popular video content platform which provides easy and fast accessibility, huge number of videos, qualified and large number of content producers, and wide range of users.
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