专业社群互动的社会网络分析--以电影产业为例
Social Network Analysis of the Professional Community Interaction -- Movie Industry Case
摘要：
随着电影制作市场竞争的兴起，由于Netflix，Hulu，HBO Max和Amazon Prime等新玩家的主要目标是制作大量独家内容以获得竞争优势，因此将不成功的标题数量降至最低是极其重要的。本文基于电影产业的社区结构，重点探讨了预测电影成功的新方法，并强调了选角导演在电影成功中的作用。基于公开可用的数据，我们创建了一个“演员”-“选角导演”-“人才代理”-“导演”的通信图，并显示使用额外的知识，导致更好的电影评级预测。
英文摘要：
With the rise of the competition in the movie production market, because of new players such as Netflix, Hulu, HBO Max, and Amazon Prime, whose primary goal is producing a large amount of exclusive content in order to gain a competitive advantage, it is extremely important to minimize the number of unsuccessful titles. This paper focuses on new approaches to predict film success, based on the movie industry community structure, and highlights the role of the casting director in movie success. Based on publicly available data we create an "actor"-"casting director"-"talent agent"-"director" communication graph and show that usage of additional knowledge leads to better movie rating prediction.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
