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

Owen Sacco; Antonios Liapis; Georgios N. Yannakakis

doi:doi:10.11648/j.mcs.20190401.13

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

Owen Sacco, Antonios Liapis, Georgios N. Yannakakis

Published in Mathematics and Computer Science (Volume 4, Issue 1)

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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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
Y1  - 2019/05/23
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

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

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Plain Text BibTeX RIS

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}
}

Copy | Download

TY  - JOUR
T1  - Extracting Semantic-Based Video Game Characters Information from Social Media Platforms
AU  - Owen Sacco
AU  - Antonios Liapis
AU  - Georgios N. Yannakakis
Y1  - 2019/05/23
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  -

Copy | Download