Identifying digital traces for business marketing through topic probabilistic model

With the exponential growth of data from social media, new opportunities for businesses to supplement marketing have been created. However, finding potential interest of consumers from a social media platform is a crucial but challenging task. Analysing the actual textual content of social media platform can help business managers to better understand the consumers’ interest for marketing. In this article, an approach was proposed to discover and quantify the business marketing topics, repost interest points on consumers and trends over time from company's micro-blog posts, furthermore gaining insights into the business marketing on social media platform. The case study results on real world data from Sina weibo show that it is useful for companies to better understand the digital traces of interaction with its consumers. The approach offers a systematic method for dealing with a large number of textual data on social media platform for business intelligence.