Where Should Existing Video Streaming Platforms Improve: A Comparative Analysis of Netflix and IQiyi

DOI

10.2991/assehr.k.211020.221How to use a DOI?

Keywords

Netflix, IQiyi, video streaming, text mining

Abstract

This study investigates two video streaming giants, Netflix and IQiyi, resorting to finding where they should improve through analyzing financial reports and the review comments from both of its apps. Statistical analysis and a deep text-mining method have been applied accordingly. Findings from financial reports reveal that Netflix has more potential in its diversification of revenue streams, and IQiyi should enlarge its business scale. Text-mining results demonstrate that both platforms need to improve in the fields of content and app features. Netflix should find ways to maintain and continue its high-quality series content, while IQiyi should expand its content library. Both platforms should work on technical problems, among which Netflix can also improve in features of personalized lists and subtitles. In addition, the subscription issue remains to be a significant problem for IQiyi, including the high price, too many layers of payment, and auto-renewal contract system. This research offers an alternative approach and a more coherent understanding of Netflix and IQiyi’s deficiencies. Methodologically, it further contributes by illustrating how review comments could be effectively applied in video-streaming related studies.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yiyun Huang
AU  - Zeyuan Lv
AU  - Zhenyuan Sui
PY  - 2021
DA  - 2021/10/21
TI  - Where Should Existing Video Streaming Platforms Improve: A Comparative Analysis of Netflix and IQiyi
BT  - Proceedings of the 2021 International Conference on Public Relations and Social Sciences (ICPRSS 2021)
PB  - Atlantis Press
SP  - 585
EP  - 592
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.211020.221
DO  - 10.2991/assehr.k.211020.221
ID  - Huang2021
ER  -