The Ubiquitous nature of smartphones has significantly increased the use of social media platforms, such as Facebook, Twitter, TikTok, and LinkedIn, etc., among the public, government, and businesses. Facebook generated ~70 billion USD in 2019 in advertisement revenues alone, a ~27% increase from the previous year. Social media has also played a strong role in outbreaks of social protests responsible for political changes in different countries. As we can see from the above examples, social media plays a big role in business intelligence and international politics. In this paper, we present and discuss a high-level functional intelligence model (recipe) of Social Media Analysis (SMA). This model synthesizes the input data and uses operational intelligence to provide actionable recommendations. In addition, it also matches the synthesized function of the experiences and learning gained from the environment. The SMA model presented is independent of the application domain, and can be applied to different domains, such as Education, Healthcare and Government, etc. Finally, we also present some of the challenges faced by SMA and how the SMA model presented in this paper solves them.

中文翻译：

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社交媒体分析的秘诀

智能手机无处不在的特性显着增加了公众、政府和企业对 Facebook、Twitter、TikTok 和 LinkedIn 等社交媒体平台的使用。Facebook 仅在 2019 年的广告收入就产生了约 700 亿美元，比上一年增长了约 27%。社交媒体在引发不同国家政治变革的社会抗议活动中也发挥了重要作用。从上面的例子中我们可以看出，社交媒体在商业智能和国际政治中发挥着重要作用。在本文中，我们提出并讨论了社交媒体分析 (SMA) 的高级功能智能模型（配方）。该模型综合输入数据并使用运营智能来提供可操作的建议。此外，它还匹配从环境中获得的经验和学习的综合功能。提出的 SMA 模型独立于应用领域，可以应用于不同的领域，例如教育、医疗保健和政府等。 最后，我们还介绍了 SMA 面临的一些挑战以及本文中提出的 SMA 模型如何解决它们。