Engaged customers are a very import part of current social media marketing. Public figures and brands have to be very careful about what they post online. That is why the need for accurate strategies for anticipating the impact of a post written for an online audience is critical to any public brand. Therefore, in this paper, we propose a method to predict the impact of a given post by accounting for the content, style, and behavioral attributes as well as metadata information. For validating our method we collected Facebook posts from 10 public pages, we performed experiments with almost 14000 posts and found that the content and the behavioral attributes from posts provide relevant information to our prediction model.

中文翻译：

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根据公司的写作方式和方式预测消费者在Facebook上的参与度

参与客户是当前社交媒体营销的重要组成部分。公众人物和品牌在网上发布内容时必须非常小心。因此，对于任何公共品牌来说，需要一种准确的策略来预测为在线读者撰写的帖子的影响至关重要。因此，在本文中，我们提出了一种通过考虑内容，样式和行为属性以及元数据信息来预测给定帖子的影响的方法。为了验证我们的方法，我们从10个公共页面上收集了Facebook帖子，我们对近14000个帖子进行了实验，发现帖子的内容和行为属性为我们的预测模型提供了相关信息。