Extracting Semantic-Based Video Game Characters Information from Social Media Platforms
Mathematics and Computer Science
Volume 4, Issue 1, January 2019, Pages: 24-40
Received: Mar. 17, 2019;
Accepted: Apr. 30, 2019;
Published: May 23, 2019
Views 342 Downloads 51
Owen Sacco, Institue of Digital Games, University of Malta, Msida, Malta
Antonios Liapis, Institue of Digital Games, University of Malta, Msida, Malta
Georgios N. Yannakakis, Institue of Digital Games, University of Malta, Msida, Malta
Character generation in video games currently relies on game developers manually creating game characters which costs in time, effort and resources. Social media, in the form of blogs, microblogs, forums, wikis, social networks and review sites contain rich information about characters in video games that are not exploited for character generation. However, such information contained in various social media applications are disconnected from one another and are not structured or enriched that can be utilised for character generation. Semantic Web techniques provide ways of linking and enriching information contained in disconnected datasets. This enriched information can be used to build complete character models for generating new characters in video games. Moreover, a video game character knowledge graph can be constructed out of the semantically-enriched information that can be used not only for character generation in video games, but also in any application that requires information about video game characters. In this paper, we present our approach for exploiting social media platforms to create semantically-enriched character models. In particular, we present our Game Character Ontology (GCO) – a light-weight vocabulary for describing character information in video games – and our methodology for extracting and describing (using our ontology) game character information from social media platforms.
Georgios N. Yannakakis,
Extracting Semantic-Based Video Game Characters Information from Social Media Platforms, Mathematics and Computer Science.
Vol. 4, No. 1,
2019, pp. 24-40.
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