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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.

Item Type: Conference or Workshop Item (Paper)

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.

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More Information

Depositing User: Kenneth McGarry

Identifiers

Item ID: 7545
URI: http://sure.sunderland.ac.uk/id/eprint/7545
Official URL: https://dblp.org/db/conf/bcshci/bcshci2017

Users with ORCIDS

ORCID for Kenneth McGarry: ORCID iD orcid.org/0000-0002-9329-9835

Catalogue record

Date Deposited: 13 Jul 2017 08:26
Last Modified: 30 Sep 2020 11:00