Discovering popular and persistent tags from YouTube trending video big dataset
Küçük Resim Yok
Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
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. Based on these advantages, YouTube datasets have a big data nature in terms of data analytics. Analyzing YouTube big datasets is essential for discovering user-video relations, video recommendation, semantic analysis of video comments and trending videos analysis. 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. In the literature, several studies are performed for sentiment analysis of YouTube video comments, video recommendation methods, and trending video analyses approaches. 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. A new algorithm is proposed, named as Popular and Persistent Tag Discovery algorithm (PPTagD algorithm), which uses proposed method. The proposed algorithm is experimentally evaluated on the dataset. The experimental results show the effectiveness of the proposed algorithm on discovering popular and persistent tags. The results reveal the tendency of United States YouTube users in terms of video tag popularity.
Açıklama
Anahtar Kelimeler
Trending video analysis, Video tag analysis, Popular and persistent tag discovery, YouTube big data analytics
Kaynak
Multimedia Tools and Applications
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
83
Sayı
4
