The advent of the social web such as twitter, facebook and the numerous social forums have provided a rich source of data representing human beliefs, social interactions and opinions that can be analysed. In this paper we show how extracting user sentiment by text mining posts from popular gaming forums can be used to identify user experience problems and issues that can adversely effect the enjoyment and gaming experience for the customers. The users posts are downloaded, preprocessed and parsed, we label the posts as negative, positive or neutral in terms of sentiment. We then identify key areas for game play improvement based on the frequency counts of keywords and key phrases used by the fora members. Furthermore, computational models based on complex network theory can rank the issues and provide knowledge about the relationships between them.
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