Human behavior is impacted by subjective states although currently the cyberspace becomes a replacement for real-life spaces and interactions. As social media platforms change people's lives and impacts the way they communicate and group themselves into virtual networks of like-minded individuals, the analysis of online content offers valuable insights of processes taking place on the Internet. Social data mining revolves around subjective content analysis, which deals with the computational processing of texts conveying people's evaluations, beliefs, attitudes and emotions. Opinion mining and sentiment analysis are the main paradigm of social media exploration and both concepts are often interchangeable. This paper investigates the use of appraisal categories to explore data gleaned for social media and describes the construction of a formal model describing the way language is used in the cyberspace to evaluate, express mood and affective states, construct personal standpoints and manage interpersonal interactions. The ontology offers a mean to investigate subjective content going beyond the traditional notions of opinion and sentiment. Pitfalls of building a formal model for appraisal categories are examined and limitations of using the model for social data exploration are discussed.