"Cultural Diversity Dilemma" Caused by Algorithm Recommendation System of Streaming Media Platform and Optimization Suggestions
Abstract
At present, the algorithm of streaming media platforms is penetrating into every smart phone user's life. With accurate user data analysis, it has significantly improved the information matching degree, but at the same time, it has also triggered the dilemma of cultural diversity. This study focuses on the essence of the cultural diversity dilemma caused by streaming media algorithm recommendation, the analysis of the user end and the optimization suggestions to break the dilemma. Through the mixed research method, it is found that user dissatisfaction stems from the sense of repetition and trapped caused by excessive accuracy; Users are not unwilling to explore, but subject to the platform search defects and the understanding threshold of niche content. Theoretically, the research no longer focuses on the accuracy of algorithm push, but focuses on the deeper dilemma of cultural diversity, trying to find a mutually inclusive balance between technical efficiency and humanistic value. In practical application, these findings can help the platform recalibrate the value orientation of the algorithm, and also provide data support for the design of some simple and easy-to-use "diversity" functions. At the same time, findings call on everyone to pay attention to the improvement of algorithm literacy, and strive to make cultural diversity truly take root on the streaming media platform.
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