TY - GEN
T1 - Application of Data Analytics for the Benchmarking of Content Genres at Video-on-Demand (VoD) Streaming Platforms
AU - Almheiri, Maryam
AU - Almemari, Maitha
AU - Ertek, Gurdal
AU - Chiravuri, Ananth
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - Video-on-Demand (VoD) streaming platforms are online services that provide on-demand access to video content, in the formats of movies and TV shows. Over the past decade, VoD platforms have experienced significant growth rates. However, there is limited understanding of the content selection strategies and processes used by these VoD services. In this study, we present our findings using a data analytics methodology developed and applied to analyze and compare the genre of content on different VoD platforms (Netflix, Amazon Prime Video, Apple TV, Disney+, HBO, and Paramount). Specifically, we analyze the distribution of genres across different platforms and identify similarities, differences, and associations. This research sheds light on the implicit content strategies of VoD platforms, provides examples of actionable insights and policy decisions, and provides a road map for future field research.
AB - Video-on-Demand (VoD) streaming platforms are online services that provide on-demand access to video content, in the formats of movies and TV shows. Over the past decade, VoD platforms have experienced significant growth rates. However, there is limited understanding of the content selection strategies and processes used by these VoD services. In this study, we present our findings using a data analytics methodology developed and applied to analyze and compare the genre of content on different VoD platforms (Netflix, Amazon Prime Video, Apple TV, Disney+, HBO, and Paramount). Specifically, we analyze the distribution of genres across different platforms and identify similarities, differences, and associations. This research sheds light on the implicit content strategies of VoD platforms, provides examples of actionable insights and policy decisions, and provides a road map for future field research.
KW - Association mining
KW - Benchmarking
KW - Data analytics
KW - Graph analytics
KW - Streaming platforms
KW - Video-on-Demand (VoD)
UR - https://www.scopus.com/pages/publications/105003879662
UR - https://www.scopus.com/pages/publications/105003879662#tab=citedBy
U2 - 10.1007/978-981-97-9559-8_22
DO - 10.1007/978-981-97-9559-8_22
M3 - Conference contribution
AN - SCOPUS:105003879662
SN - 9789819795581
T3 - Lecture Notes in Networks and Systems
SP - 253
EP - 263
BT - Intelligent Sustainable Systems - Selected Papers of WorldS4 2024
A2 - Nagar, Atulya
A2 - Jat, Dharm Singh
A2 - Mishra, Durgesh
A2 - Joshi, Amit
PB - Springer Science and Business Media Deutschland GmbH
T2 - 8th World Conference on Smart Trends in Systems Security and Sustainability, WorldS4 2024
Y2 - 23 July 2024 through 26 July 2024
ER -