The goal of this project is to produce a programming framework for the social interaction side of knowledge processing. We aim at making museum content available outside of the Amsterdam Museum by detecting conversational topics on social media and their corresponding emotional/ engagement level. We use API’s for Facebook, Twitter and Google Places to access information about the users specific location and preferences linked to the four values of DNA. Via several classification methods, we distinguish between relevant and irrelevant information. Relevant information consists of posts, hashtags and retweets of the user containing a multitude of keywords related to DNA. The irrelevant information embodies marketing post made by corporations and spam and are not taken into account. As collecting and classifying the via social media gathered data occurs at an early stage, our group is located in the front of the chain collaboration. Our main goal is to gather and classify the filtered relevant information and pass this on to the second in chain for further processing, this would be the story engine group who can use this to create situation-specific stories in real-time and possibly the presentation groups.