首页> 外文会议>2016 International Conference on Internet of Things and Applications >Relationships between classical factors, social factors and box office collections
【24h】

Relationships between classical factors, social factors and box office collections

机译:古典因素,社会因素与票房收藏之间的关系

获取原文
获取原文并翻译 | 示例

摘要

Every year the number of movie produced and released surpass the previous year's count and so do the total box office collections. So in this quality centric industry, it becomes imperative that the movie succeeds both in terms of box office collections and critical reviews and also renders profit. Due to advent of predictive analytics and big data generated through various social interactions, models to predict accurately the total gross of a movie can be devised, which eventually help the movie studio by giving constructive feedback both in pre-production and post-production phase. So the availability of this data gathered from various social platforms like IMDb, YouTube and Wikipedia can help to gauge the society's reaction and response towards a particular movie. It can also foretell a society's anticipation towards a particular movie. In this paper, we have built predictive models by establishing links between classical features, social media features and the overall success of the movie which includes total box office collection and the critics rating or review. The results show that the prediction model built using integration of classical as well as social factors can achieve higher accuracy rate.
机译:每年制作和发行的电影数量都超过上一年的数量,总票房也是如此。因此,在这个以质量为中心的行业中,当务之急是电影必须在票房收入和评论方面都取得成功,并且要赚钱。由于出现了预测分析和通过各种社交互动生成的大数据,因此可以设计出可以准确预测电影总票房的模型,最终可以通过在制作前和制作后阶段提供建设性反馈来帮助电影制片厂。因此,从IMDb,YouTube和Wikipedia等各种社交平台收集的这些数据的可用性可以帮助评估社会对特定电影的反应。它还可以预示社会对特定电影的期待。在本文中,我们通过建立古典特征,社交媒体特征与电影的整体成功(包括总票房和评论家的评分或评论)之间的联系来建立预测模型。结果表明,结合经典因素和社会因素建立的预测模型可以达到较高的准确率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号