Computational methods for text mining user posts on a popular gaming forum for identifying user experience issues.

McGarry, Kenneth and McDonald, Sharon (2017) Computational methods for text mining user posts on a popular gaming forum for identifying user experience issues. In: British HCI 2017 Conference Digital Make Believe, 3-6 Jul 2017, Sunderland, UK. (In Press)

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Abstract

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.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computing > Artificial Intelligence
Computing > Human-Computer Interaction
Computing
Divisions: Faculty of Health Sciences and Wellbeing
Depositing User: Kenneth McGarry
Date Deposited: 13 Jul 2017 08:26
Last Modified: 13 Jul 2017 08:26
URI: http://sure.sunderland.ac.uk/id/eprint/7545

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