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Analysing medical social media data gains in importance given an increased availability of such data. In this paper, we analyse the language of medical blogs by means of a sublanguage analysis. More specifically, verb usage, semantic categories of used words as well as co-occurrence patterns are determined by means of natural language processing tools. The results show that in this text type, many concepts refer to the semantic categories Living Beings and Chemicals and Drugs. In contrast to clinical documents, the spectrum of verbs in blogs is very broad creating semantic relations of different types. From these language characteristics, we conclude for automatic processing tools for medical blogs that methods for reference resolution and for relation extraction where the relation type does not need to be specified in advance are required.

Sublanguage Analysis of Medical Weblogs