基于神经网络的CEO表情分析及其对发布会媒体关注度的影响

CEO Facial Expression Analysis Based on Neural Networks and Its Impacts on Media Attention at Press Conferences

【目的】基于神经网络检测实时视频流中的人脸表情以探究CEO在产品发布会上的情绪特征与媒体关注度的关联。【方法】收集34家电子产品公司566场产品发布会视频,通过MTCNN等模型对产品发布会上CEO的表情进行检测,结合统计学分析方法对CEO的情绪表达模式进行探究,并采用关联性分析的方法探究CEO情绪特征对发布会媒体关注度的影响。【结果】不同公司CEO在发布会中存在迥异的情绪表达模式,可聚集为与企业主营产品类型密切关联的若干类簇,各类簇中也存在截然不同的情绪惯性表达以及影响趋势,且愤怒情绪占比与发布会媒体关注度均在95%置信度下显著正相关(Pearson相关系数均大于0.21)。【局限】仅面向电子产品发布会,所采集的各公司数据分布也不均匀。【结论】应用深度学习实现了基于视频流的CEO表情快速检测,分析了CEO情绪表达模式及其影响,提出了CEO情绪管理对品牌传播等的建议。

[Objective]This paper uses neural networks to detect facial expressions in real-time video streams,aiming to explore the correlation between CEO’s emotional characteristics at product launch events and media attention.[Methods]A total of 566 product launch event videos from 34 electronics companies were collected.Facial expressions of CEOs during the events were detected using models like MTCNN.Then,we investigated the patterns of CEO’s emotional expressions and explored the influence of their characteristics on media attention with correlation analysis.[Results]CEOs of different companies exhibited distinct emotional expression patterns during the launch events,which could be clustered closely associated with the main product types of the companies.Each cluster also had significant emotional inertia expression and influence trends.The proportion of anger was positively correlated with media attention during the launch events at a confidence level of 95%(with Pearson’s correlation coefficients exceeding 0.21).[Limitations]This study focuses on electronic product launch events,and the collected data from various companies were not unevenly distributed.[Conclusions]Deep learning enable the rapid detection of CEO facial expressions based on video streams.This study analyzed CEO’s emotional expression patterns and their influence and provided suggestions for CEO’s emotional management in brand communication.