预测电影票房的技术使用神经网络和情绪挖矿
Zhuqing Zhang1, Yutong Meng2, Daibai Xiao3
1School of Journalism and Communication, Nanjing University, Nanjing, 210093, Jiangsu, China. jessiezhang@smail.nju.edu.cn.
Scientific reports
|September 11, 2024
概括
准确的电影票房预测通过结合观众评论而得到增强. 这项研究将文本分析与机器学习模型 (如卷积神经网络 (CNN)) 整合在一起,以显著提高电影投资的预测准确性.
科学领域:
- 数据科学数据科学数据科学
- 计算语言学 计算语言学
- 电影研究 电影研究
背景情况:
- 电影票房预测对于投资,发行和安排至关重要,但由于影响因素有限,目前的模型缺乏准确性.
- 现有的预测模型往往忽视了观众电影评论中包含的宝贵见解.
- 在11个类别中,确定了34个影响因素的综合集,这些因素可能会影响票房表现.
研究的目的:
- 通过结合观众情绪分析,开发一个改进的电影票房预测模型.
- 用各种机器学习技术调查电影评论对预测准确性的影响.
- 为电影业和管理部门提供决策参考.
主要方法:
- 利用Word2vec从电影域名中提取特征,并创建了形容词/动词的情感字典.
- 应用TF-IDF来计算电影评论中的情感分数.
- 开发了使用多变量线性回归 (MLR) 和卷积神经网络 (CNN) 的预测模型,整合了来自评论的特征.
主要成果:
- 没有评论集成的卷积神经网络 (CNN) 模型实现了71.9%的预测准确度.
- 整合观众评论显著提高了预测准确度:MLR准确度增加了16.1%,CNN准确度增加了11.8%.
- 这项研究表明,结合评论情绪分析可以显著提高票房预测模型的可靠性.
结论:
- 观众的评论是提高电影票房预测准确性的重要,以前未被充分利用的功能.
- 机器学习模型,特别是CNN,结合评论中的情绪分析,为票房预测提供了一种强大的方法.
- 这些发现为优化电影行业投资和战略规划提供了可操作的见解.
相关概念视频
01:07End Point Prediction: Gran Plot
299
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
For potentiometric titration, the Gran plot is created by plotting...
299
01:03Prediction Intervals
2.2K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.2K
01:20Labeling Emotion
116
Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
116