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Extracting Semantic-Based Video Game Characters Information from Social Media Platforms

Received: 17 March 2019     Accepted: 30 April 2019     Published: 23 May 2019
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Abstract

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.

Published in Mathematics and Computer Science (Volume 4, Issue 1)
DOI 10.11648/j.mcs.20190401.13
Page(s) 24-40
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Vocabularies, Ontologies, Semantic Web, Computer Games Technology, Procedural Content Generation

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Cite This Article
  • APA Style

    Owen Sacco, Antonios Liapis, Georgios N. Yannakakis. (2019). Extracting Semantic-Based Video Game Characters Information from Social Media Platforms. Mathematics and Computer Science, 4(1), 24-40. https://doi.org/10.11648/j.mcs.20190401.13

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    ACS Style

    Owen Sacco; Antonios Liapis; Georgios N. Yannakakis. Extracting Semantic-Based Video Game Characters Information from Social Media Platforms. Math. Comput. Sci. 2019, 4(1), 24-40. doi: 10.11648/j.mcs.20190401.13

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    AMA Style

    Owen Sacco, Antonios Liapis, Georgios N. Yannakakis. Extracting Semantic-Based Video Game Characters Information from Social Media Platforms. Math Comput Sci. 2019;4(1):24-40. doi: 10.11648/j.mcs.20190401.13

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  • @article{10.11648/j.mcs.20190401.13,
      author = {Owen Sacco and Antonios Liapis and Georgios N. Yannakakis},
      title = {Extracting Semantic-Based Video Game Characters Information from Social Media Platforms},
      journal = {Mathematics and Computer Science},
      volume = {4},
      number = {1},
      pages = {24-40},
      doi = {10.11648/j.mcs.20190401.13},
      url = {https://doi.org/10.11648/j.mcs.20190401.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mcs.20190401.13},
      abstract = {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.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Extracting Semantic-Based Video Game Characters Information from Social Media Platforms
    AU  - Owen Sacco
    AU  - Antonios Liapis
    AU  - Georgios N. Yannakakis
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    PY  - 2019
    N1  - https://doi.org/10.11648/j.mcs.20190401.13
    DO  - 10.11648/j.mcs.20190401.13
    T2  - Mathematics and Computer Science
    JF  - Mathematics and Computer Science
    JO  - Mathematics and Computer Science
    SP  - 24
    EP  - 40
    PB  - Science Publishing Group
    SN  - 2575-6028
    UR  - https://doi.org/10.11648/j.mcs.20190401.13
    AB  - 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.
    VL  - 4
    IS  - 1
    ER  - 

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Author Information
  • Institue of Digital Games, University of Malta, Msida, Malta

  • Institue of Digital Games, University of Malta, Msida, Malta

  • Institue of Digital Games, University of Malta, Msida, Malta

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