Laboratories in Quebec Video Gaming Industry and University Partnerships
The Example of Game Practices and Gamer Communities Research, and the Future Brought by Artificial Intelligence
Keywords:
Research laboratory, videogame industry, partnerships, user testing, game analytics, game practices, gaming communities, artificial intelligenceAbstract
Given the large production of video games in Quebec, the province has been able to develop an exceptional context of research partnerships between video game companies and university laboratories, each of which has developed an expertise specific to their field. In this article, the following question will first be asked: what kind of research is carried out in companies? The objective is not to make a systematic survey of the various forms of research carried out within all companies located in Quebec, but rather to identify the main realities experienced in gaming companies in order to answer a second question: what kind of research is not carried out those companies? The answer will be used to illustrate possible partnerships with researchers interested in gaming practices and in gaming communities, a research theme that is not often addressed by companies. Among the university gaming laboratories in Montreal, the example of the laboratory of the Université du Québec à Montréal will be briefly presented in order to situate researches that explicitly aims to understand identification, communication and social dynamics of gaming communities. The article concludes with an exposition of some of the future perspectives of research in this field, mainly related to the development of artificial intelligence and machine learning.
References
Association canadienne du logiciel de divertissement (2019). Le secteur canadien du jeu vidéo 2019, Nordicity, Ottawa. En ligne :
https://theesa.ca/wp-content/uploads/2019/11/Secteurcanadiendujeuvideo2019_FR.pdf.
Balci, K. et Salah, A.A. (2015). Automatic Analysis and Identification of Verbal Aggression and Abusive Behaviors for Online Social Games. In Computers in Human Behavior, 53, 517-526.
Bates, B. (2004). Game Design (Second Edition), Boston, Thomson Course Technology.
Berendt, B., Büchler, M. et Rockwell, G. (2015). Is it Research or is it Spying? Thinking-Through Ethics in Big Data AI and Other Knowledge Sciences. In Künstliche Intelligenz, 29(2), 223-232.
Bonenfant, M., Richert, F. et Deslauriers, P. (2017). Using Big Data Tools and Techniques to Study a Gamer Community: Technical, Epistemological, and Ethical Problems. In Loading… CGSA Journal, 11(16), p. 87-108. En ligne : https://journals.sfu.ca/loading/index.php/loading/article/view/174/208.
Bonenfant, M. et Meurs, M.-J. (2019). Collaboration Between Social Sciences and Computer Science: Towards a Cross-disciplinary Methodology for Studying Big Social Data from Online Communities. In Handbook of Internet Research II, New York: Springer, 47-63.
Bonenfant, M., Crémier, L. et Lafrance Saint-Martin, L.I. (2018). Quelques réflexions sémiotiques sur le circuit des données massives. In Big Data et société: Industrialisation des médiations symboliques, Québec : Presses Universitaires du Québec, collection Communication, 151-184.
Bonenfant, M., Deslauriers, P. et Heddad, I. (2019). Methodological and Epistemological Reflections on the Use of Game Analytics Towards Understanding the Social Relationships of a Video Game Community. In Data Analytics Applications in Gaming & Entertainment, New York: CRC Press, Taylor & Francis Group, coll. Data Analytics Applications, 180-202.
Bonenfant, M., Crémier, L. et Lafrance Saint-Martin, L.I. (2019). Raw Data or Hypersymbols? Modelizing Sign Function in Big Data Meaning-making Processes, Semiotica, Berlin:De Gruyter.
Chen, Z., Hendrix, W. et Samatova, N.F. (2011). Community-based Anomaly Detection in Evolutionary Networks, Berlin: Springer Science.
Comission d'accès à l'information du Québec (2018). Nouveau règlement européen sur la protection des données personnelles, http://www.cai.gouv.qc.ca/nouveau-reglement-europeen-sur-la-protection-des-donnees-personnelles/ consulté le 20 mai 2019.
Cornuéjois, A., Miclet, L. et Kodratoff, Y. (2002). Apprentissage artificiel : Concepts et algorithmes, Paris : Eyrolles.
De Castell, S., Jensen, J., Taylor, N. et Weiler, M. (2012). Theoretical and Methodological Challenges (and Opportunities) in Virtual Worlds Research, Proceedings of the International Conference on the Foundations of Digital Games, New-York: ACM, 134-140.
Debeauvais, T., Lopes, C.V., Yee, N. et Ducheneaut (2014). Retention and Progression: Seven Months in World of Warcraft, Proceedings of the 9th International Conference on the Foundations of Digital Games, Fort Lauderdale.
Drachen, A., Mirza-Babaei, P. et Nacke, L. (2018). Games User Research, Londres: Oxford University Press, 2018.
Ducheneaut, N. et Moore, R.J. (2004). The Social Side of Gaming: A Study of Interaction Patterns in a Massively Multiplayer Online Game, Proceedings of the 2004 ACM Conference on Computer Supported Cooperative Work, Chicago, 360-369.
El-Nasr, M.S., Drachen, A. et Canossa, A. (2013). Introduction. In Game Analytics: Maximizing the Value of Player Data, Londres: Springer, 3-12.
Fields, T.V. (2013). Game Industry Metrics Terminology and Analytics Case Study. In Game Analytics: Maximizing the Value of Player Data, Londres: Springer, 53-71.
Godse, M. et Mulik, S. (2009). An Approach for Selecting Software-as-a-Service (SaaS) Product, 2009 IEEE International Conference on Cloud Computing, Washington, 155-158. En ligne : http://barbie.uta.edu/~hdfeng/CloudComputing/cloud/cloud29.pdf.
Hutto, C.J. et Gilbert, E. (2015). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text, Proceedings of the Eighth International AAAI Conference on Weblogs and Social Media, Ann Arbor, p. 216-225. En ligne : https://www.aaai.org/ocs/index.php/ICWSM/ICWSM14/paper/download/8109/8122/.
Kirman, B., Lawson, S. et Linehan, C. (2009). Gaming on and off the Social Graph: The Structure of Facebook Games, Lincoln, Lincoln Social Computing Research Center.
Kulikowski, C.A. et Weiss, S.M. (1992). Computer Systems That Learn, Burlington: Morgan Kaufmann.
Kwak, H. et Blackburn, J. (2014). Linguistic Analysis of Toxic Behaviour in an Online Video Game, Proceedings of the 2014 International Conference on Social Informatics, Barcelone, 209-217.
Mackworth, A.K. et Poole, D.L. (2017). Artificial Intelligence: Foundations of Computational Agents (2nd), New York: Cambridge University Press.
Meisel, W.S. (1972). Computer-Oriented Approaches to Pattern Recognition, New York, Academic Press.
Merritt, S. et Clauset, A. (2013). Social Network Dynamics in a Massive Online Game: Network Turnover, Non-Densification, and Team Engagement in Halo Reach, Stanford, Stanford University.
Mirza-Babaei, P., Long, S., Foley, E. et McAllister, G. (2011). Understanding the Contribution of Biometrics to Games User Research, DiGRA/Utrecht School of the Arts, 6. En ligne : http://www.digra.org/wp-content/uploads/digital-library/11310.43254.pdf.
Mirza-Babaei, P., Moosajee, N. et Drenikow, B. (2017). Playtesting for Indie Studios, AcademicMindtrek’16, Tempere, 366-374.
Mullen, T. et Malouf, R. (2006). A Preliminary Investigation into Sentiment Analysis of Informal Political Discourse, Proceedings of the AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs, Palo Alto, p. 159-162. En ligne : https://www.aaai.org/Papers/Symposia/Spring/2006/SS-06-03/SS06-03-031.pdf.
Nasukawa, T. et Yi, J. (2003). « Sentiment Analysis: Capturing Favorability Using Natural Language Processing », Proceedings of the 2nd International Conference on Knowledge Capture, Sanibel Island, 70-77.
Newman, M. E. J. (2004). Fast Algorithm for Detecting Community Structure in Networks, Ann Arbor:University of Michigan.
Prasad, S. et Khilnani, D. (2010). Facebook Game Network Analysis, Stanford: Stanford University.
Pustejovsky, J. et Stubbs, A. (2013). Natural Language Annotation for Machine Learning, Sebastopol, O’Reilly Media.
Radmacher, F.G. et Thomas, W. (2008). A Game Theoretic Approach to the Analysis of Dynamic Networks. In ScienceDirect, Elsevier, 200(2), 21-37.
Revenu Québec (2018). Crédit d’impôt pour des titres multimédias, En ligne : https://www.revenuquebec.ca/fr/entreprises/impots/impot-des-societes/credits-dimpot-des-societes/credits-auxquels-une-societe-peut-avoir-droit/credit-dimpot-pour-des-titres-multimedias/ consulté le 13 février 2021.
Saint-Charles, J., & Mongeau, P. (2018). Social influence and discourse similarity networks in workgroups. In Social Networks, 52, 228-237.
Shen, J., Brdiczka, I., Ducheneaut, N., Yee, N. et Begole, B. (2012). Inferring Personality of Online Gamers by Fusing Multiple-View Predictions, Proceedings of the 20th International Conference, User Modeling, Adaptation, and Personalization, Montréal.
Sotamaa, O. (2010) « Introduction ». In Games as Services: Final Report, Tampere: University of Tampere, 3-10.
Strååt, B. & Verhagen, H. (2017). Using User Created Game Reviews for Sentiment Analysis: A Method for Researching User Attitudes, GHITALY17: 1st Workshop on Games-Human Interaction, Cagliari, 7-12. En ligne :
http://ceur-ws.org/Vol-1956/GHItaly17_paper_01.pdf.
Sweeney, L. (2013). Discrimination in Online Ad Delivery, Cambridge: Harvard University
TECHNOCompétences (2018). Profil de la main-d’œuvre dans l’industrie du jeu électronique au Québec en 2016, Comité sectoriel de main-d’œuvre en technologies de l’information et des communication, Université McGill, Montréal.
Thompson, J.J., Leung, B.H.M., Blair, M.R. et Taboada, M. (2017). Sentiment Analysis of Player Chat Messaging in the Video Game StarCraft 2: Extending a Lexicon-based Model ». In ScienceDirect, Elsevier, 137(1), 149-162.
Tyugu, E. (2007). Algorithms and Architectures of Artificial Intelligence, Amsterdam: IOS Press.
Wachter-Boettcher, S. (2017). Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech. New York, WW Norton & Company.
Wang, M. et Chen, J. (2014). CoDEM: An Ingenious Tool of Insight into Community Detection in Social Networks, Proceedings of the ACM International Conference on Information and Knowledge Management, Shanghai, 2006-2008.
Whitson, J.R. (2012). Game Design by Numbers: Instrumental Play and the Quantitative Shift in the Digital Game Industry, PhD Thesis (sociologie), Ottawa: Carleton University.
Witkowski, W. (2021). Videogames are a bigger industry than movies and North American sports combined, thanks to the pandemic. En ligne : https://www.marketwatch.com/story/videogames-are-a-bigger-industry-than-sports-and-movies-combined-thanks-to-the-pandemic-11608654990
Downloads
Published
Issue
Section
License
Copyright (c) 2021 Maude Bonenfant, Jonathan Bonneau
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The copyright for work in this journal is retained by the author(s), with first publication rights granted to the journal. In keeping with a Creative Commons license, articles are free to use with proper attribution (to both the author and Loading…) for educational and other non-commercial uses.