Relation extraction in documents allows the detection of how entities being discussed in a document are related to one another (e.g. part-of). This paper presents an analysis of a relation extraction system based on prior work but applied to the J.D. Power and Associates Sentiment Corpus to examine how the system works on documents from a range of social media. The results are examined on three different subsets of the JDPA Corpus, showing that the system performs much worse on documents from certain sources. The proposed explanation is that the features used are more appropriate to text with strong editorial standards than the informal writing style of blogs.