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Academic Journal of Business & Management, 2020, 2(4); doi: 10.25236/AJBM.2020.020406.

Research on Self-media Original Video Protection Based on Machine Learning——Based on the original author's perspective

Author(s)

Fan Wu1, Wenxin Guan2, Shouyu Wei3

Corresponding Author:
Fan Wu
Affiliation(s)

1. School of Applied Mathematics, Anhui University of Finance and Economics
2. School of Business Administration, Anhui University of Finance and Economics
3. School of Finance, Anhui University of Finance and Economics

Abstract

In order to understand the willingness of self-media video users to protect the copyright of original videos and the improvement direction of the self-media video ecosystem, 1,500 questionnaires were actually distributed to users on the entire network video platform as survey objects to obtain sample data, and the rights of authors were affected by machine learning. In-depth analysis of the factors of will, we mainly found that although the benefits obtained by plagiarists and the cost of video production can most stimulate the author's willingness to defend rights, this is not controllable. Therefore, we believe that reducing the cost of rights protection (the second most important) is the most feasible direction to increase the author's willingness to protect rights. In addition, it is also found that the support of the platform and the report of the audience will have a direct impact on all factors, and the feedback factor and cost factor will have a direct impact on the induction factor. Finally, we made corresponding suggestions.

Keywords

Self-media video ecosystem; rights protection; machine learning; Python

Cite This Paper

Fan Wu, Wenxin Guan, Shouyu Wei. Research on Self-media Original Video Protection Based on Machine Learning——Based on the original author's perspective. Academic Journal of Business & Management (2020) Vol. 2, Issue 4: 53-63. https://doi.org/10.25236/AJBM.2020.020406.

References

[1] Zhu Chen. Research on the Copyright Protection of Online Short Video [J]. Legal System and Society, 2020 (05): 62-63.
[2] Cong Lixian. The core issues of short video copyright protection [J]. Publication Reference, 2019 (03): 1.
[3] Wu Fan, Li Chunzhong, Lin Lifang, Zhu Jiaming. Research on a crowd evacuation simulation algorithm based on cellular automata [J]. Journal of Yanbian University (Natural Science Edition), 2019, 45(04):329-334.