Social Media Tycoon is a game-based learning project with the goal of improving awareness of the perils of social media among public servants.
We live in a world with ubiquitous social media, where there is a platform for almost every niche. Interested in books? Then goodreads is the social media for you. Interested in sharing photos? Then Instagram has you covered. The common theme among these social media platforms is that they are free. However, the companies behind these apps are amongst the biggest in the world, how can that happen? Most users have some understanding of the concept of ‘if it is free then your data is the product’, the business model that most social media networks employ but most users do not understand what that means for the privacy of their data (Fiesler & Hallinan, 2018). To address the gap in knowledge, Social Media Tycoon will allow the player takes the reins of a social media company.
The game aims to be beneficial to the Public Service by reducing potential political embarrassment caused by inadvertent releases of information. For the player, the aim is to reduce the risk of them oversharing information on social media, thereby reducing the risk of personal embarrassment and potential harm.
Self-reflection by users is more likely to occur if they have a chance to look ‘behind the curtain’ of a social media company (Gee, 2003; Shklovski, Mainwaring, Skúladóttir, & Borgthorsson, 2014). Normally, users only use social media from their own perspective and may not question what they are sharing and where that data may end up (Fiesler, Lampe, & Bruckman, 2016). The game aims to change this lack of reflection by giving users an understanding of how social media companies make money and how they treat your data depending on the company’s location.
Game Design Principles
The game-design principles are based on the framework of Perrotta et. al (2013). This framework provides clear definitions and detailed research.
The game rules mean the player must make decisions that will positively or negatively impact one of four scales: account balance, privacy, app desirability and users. To win, the player must get their account balance to a certain level. The simplicity of the rules will help users to understand the game quickly and is suited to the relatively short time-frame users will have to play the game during in-work training.
The game’s win-state is clear but challenging. In order to achieve the goal, players will have to make choices that sacrifice the ‘privacy’ of their pretend user-base, something that they may be against their real-world moral compass triggering greater metacognition (Gee, 2003).
The game’s authenticity comes from its setting of a social media company and the use of an adventure style interface. Although some of the decisions the players can choose may be a little absurd or direct the concepts and outcomes of the decisions are based on real-world examples of social media companies.
Despite the games reliance on real world examples the drive to make as much money as possible allows the player to abandon the need to consider others in the pursuit of financial gain. This fictional approach is aimed at getting the player in to the mindset of those that value financial profit above all (Bogost, 2011).
The game aims to make balancing the various scoreboard items challenging but possible. Many of the decisions that increase income, reduce privacy. When privacy gets too low, the player is punished by a reduction in income. The complex requirement to balance income, privacy, coolness and user numbers means that users cannot just use a ‘first order optimal strategy’ to win. To make the game enticing the user will not be punished immediately and will often make a number of decisions before experiencing any punishment. This is to ensure the player can develop an understanding of the game and a desire to keep playing.
The game does not have an inbuilt social element due to the time constraints and limits of the chosen platform. However, players would be playing the game in the same room giving them the opportunity to discuss and bond over shared experience.
The game aims to introduce enjoyment and fun through comical choices that make the player laugh. The goal is to balance realistic decisions and the absurd to ensure that the user is made to feel safe (Bogost, 2011). In some user choices, the outcome is based on chance. This provides a degree of uncertainty and unpredictability to the game as even if you make the same decision you may end up with a different outcome.
Intrinsic motivation is provided by regular score updates. Notifications provide players with immediate and constructive feedback, helping them to understand the consequences of their decisions and refine their strategy (Klimmt & Hartmann, 2006).
Players can customise their experience by adding their name and the name of the app. The narrative of the game is non-linear, allowing players to choose their own path through the game, giving them agency in the game-play (Perrotta, Featherstone, Ashton, & Houghton, 2013). The win-state is based on income level but that can be achieved in one of many combinations of choices allowing the This game to becan be replayed with different outcomes.
Bogost, I. (2011). How to do things with videogames. Minneapolis: University of Minnesota Press.
Fiesler, C., & Hallinan, B. (2018). We Are the Product: Public Reactions to Online Data Sharing and Privacy Controversies in the Media. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (p. 53). ACM.
Fiesler, C., Lampe, C., & Bruckman, A. S. (2016). Reality and perception of copyright terms of service for online content creation. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing (pp. 1450–1461). ACM.
Gee, J. P. (2003). What video games have to teach us about learning and literacy. Computers in Entertainment (CIE), 1(1), 20–20.
Klimmt, C., & Hartmann, T. (2006). Effectance, self-efficacy, and the motivation to play video games. In P. Vorderer & J. Bryant (Eds.), Playing video games: Motives, responses, and consequences (pp. 133–145). New York; London: Routledge.
Perrotta, C., Featherstone, G., Ashton, H., & Houghton, E. (2013). Game-based Learning: Latest Evidence and Future Directions (NFER Research Programme: Innovation in Education). Slough: NFER. Retrieved from https://www.nfer.ac.uk/publications/GAME01/GAME01_home.cfm
Shklovski, I., Mainwaring, S. D., Skúladóttir, H. H., & Borgthorsson, H. (2014). Leakiness and creepiness in app space: Perceptions of privacy and mobile app use. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 2347–2356). ACM.