BEET: Behavior Engagement Emotion Trigger – A AI-based model to maximize audience engagement
Wael Maged Badawy · Menoufia Journal of Electronic Engineering Research · 2021
Engagement and measuring is a key performance for any content. The wide spread of the Internet and the adoption in our daily life, audience has many options to explore and audience developed the power of rejection. This power of rejection reduces the time of exposure and engagement to any contents including the in person engagement. The access to the online tools and portals provide an escape route from human-tohuman interaction. A new tool to maximize audience engagement to a content that can influence a decision becomes a key performance and an asset for exposure. It enables a better delivery of the Contents, an increased interaction with the content, simplify the process of creating an engaging content, and maximize the exposure time. This paper presents a prototype, and evaluation of the performance of an automated Content Behavior Emotion Engagement Model “BEEM” that uses Deep Learning and Big Data analysis to discover the Behavior Emotion trend of the audience. BEETAIR is a new innovative framework that will transform the media market through Behavior Emotion Engagement Trigger Analyzer, and Intelligent Recommender. It uses The Artificial Intelligent-based Dialogue Generator for Maximum Audience Engagement