Playing Conspiracy

Introduction Scholars, journalists, conspiracists, and public-facing groups have employed a variety of analogies to discuss the role that misleading content (conspiracy theory, disinformation, malinformation, and misinformation), plays in our everyday lives. Terms like the “disinformation war” (Hwang) or the “Infodemic” (United Nations) attempt to summarise the issues of misleading content to aide public understanding. This project studies the effectiveness of these analogies in conveying the movement of online conspiracy theory in social media networks by simulating them in a game. Building from growing comparisons likening conspiracy theories to game systems (Berkowitz; Kaminska), we used game design as a research tool to test these analogies against theory. This article focusses on the design process, rather than implementation, to explore where the analogies succeed and fail in replication. Background and Literature Review Conspiracy Theories and Games Online conspiracy theories reside in the milieu of misinformation (unintentionally incorrect), disinformation (intentionally incorrect), and malinformation (intentionally harmful) (Wardle and Derakhshan 45). They are puzzled together through the vast amount of information available online (Hannah 1) creating a “hunt” for truth (Berkowitz) that refracts information through deeply personal narratives that create paradoxical interpretations (Hochschild xi). Modern social media networks offer curated but fragmented content distribution where information discovery involves content finding users through biased sources (Toff and Nielsen 639). This puzzling together of theories gives conspiracy theorists agency in ‘finding the story’, giving them agency in a process with underlining goals (Kaminska). A contemporary example is QAnon, where the narrative of a “secret global cabal”, large-scale pedophile rings, and overstepping government power is pieced together through Q-drops or cryptic clues that users decipher (Bloom and Moskalenko 5). This puzzle paints a seemingly hidden reality for players to uncover (Berkowitz) and offers gripping engagement which connects “disparate data” into a visualised conspiracy (Hannah 3). Despite their harmful impacts, conspiracy theories are playful (Sobo). They can be likened to playful acts of make-belief (Sobo), reality-adjacent narratives that create puzzles for exploration (Berkowitz), and community building through playful discovery (Bloom and Moskalenko 169). Not only do conspiracies “game the algorithm” to promote content, but they put players into in a self-made digital puzzle (Bloom and Moskalenko 17, 18). This array of human and nonhuman actors allows for truth-spinning that can push people towards conspiracy through social bonds (Moskalenko). Mainstream media and academic institutions are seen as biased and flawed information sources, prompting these users to “do their own research” within these spaces (Ballantyne and Dunning). However, users are in fragmented worldviews, not binaries of right and wrong, which leaves journalism and fact-checkers in a digital world that requires complex intervention (De Maeyer 22). Analogies Analogies are one method of intervention. They offer explanation for the impact conspiracy has had on society, such as the polarisation of families (Andrews). Both conspiracists and public-facing groups have commonly used an analogy of war. The recent pandemic has also introduced analogies of virality (Hwang; Tardáguila et al.). A war analogy places truth on a battleground against lies and fiction. “Doing your own research” is a combat maneuver for conspiracy proliferation through community engagement (Ballantyne and Dunning). Similarly, those fighting digital conspiracies have embraced the analogy to explain the challenges and repercussions of content. War suggests hardened battlelines, the need for public mobilisation, and a victory where truth prevails, or defeat where fallacy reigns (Shackelford). Comparatively, a viral analogy, or “Infodemic” (United Nations), suggests misleading content as moving through a network like an infectious system; spreading through paths of least resistance or effective contamination (Scales et al. 678; Graham et al. 22). Battlelines are replaced with paths or invasion, where the goal is to infect the system or construct a rapid response vaccine that can stymie the ever-growing disease (Tardáguila et al.). In both cases, victorious battles or curative vaccinations frame conspiracy and disinformation as temporary problems. The idea of the rise and falls of a conspiracy’s prominence as link to current events emulates Byung-Chung Han’s notion of the digital swarm, or fragmented communities that coalesce, bubble up into volatile noise, and then dissipate without addressing the “dominant power relations” (Han 12). For Han, swarms arise in digital networks with intensive support before disappearing, holding an influential but ephemeral life. Recently, scholarship has applied a media ecology lens to recognise the interconnection of actors that contribute to these swarms. The digital-as-ecosystem approach suggests a network that needs to be actively managed (Milner and Phillips 8). Tangherlini et al.’s work on conspiracy pipelines highlights the various actors that move information through them to make the digital ecosystem healthy or unhealthy (Tangherlini et al.). Seeing the Internet, and the movement of information on it, as an ecology posits a consideration of processes that are visible (i.e., conspiracy theorists) and invisible (i.e., algorithms etc.) and is inclusive of human and non-human actors (Milner and Phillips). With these analogies as frames, we answer Sobo’s call for a playful lens towards conspiracy alongside De Maeyer’s request for serious interventions by using serious play. If we can recognise both conspiracy and its formation as game-like and understand these analogies as explanatory narratives, we can use simulation game design to ask: how are these systems of conspiracy propagation being framed? What gaps in understanding arise when we frame conspiracy theory through the analogies used to describe it? Method Research-Creation and Simulation Gaming Our use of game design methods reframed analogies through “gaming literacy”, which considers the knowledge put into design and positions the game as a set of practices relating to the everyday (Zimmerman 24). This process requires constant reflection. In both the play of the game and the construction of its parts we employed Khaled’s critical design framework (10-11). From March to December 2021 we kept reflective logs, notes from bi-weekly team meetings, playtest observations, and archives of our visual design to consistently review and reassess our progression. We asked how the visuals, mechanics, and narratives point to the affordances and drawbacks of these analogies. Visual and Mechanical Design Before designing the details of the analogies, we had to visualise their environment – networked social media. We took inspiration from existing visual representations of the Internet and social media under the hypothesis that employing a familiar conceptual model could improve the intelligibility of the game (figs. 1 and 2). In usability design, this is referred to as "Jakob's law" (Nielsen), in which, by following familiar patterns, the user can focus better on content, or in our case, play. Fig. 1: “My Twitter Social Ego Networks” by David Sousa-Rodrigues. A visual representation of Sousa-Rodrigues’s social media network. <https://www.flickr.com/photos/11452351@N00/2048034334>. We focussed on the networked publics (Itō) that coalesce around information and content disclosure. We prioritised data practices that influence community construction through content (Bloom and Moskalenko 57), and the larger conspiracy pipelines of fragmented data (Tangherlini et al. 30). Fig. 2: "The Internet Map" by Ruslan Enikeev. A visual, 2D, interactive representation of the Internet. <http://internet-map.net/>. Our query focusses on how play reciprocated, or failed to reciprocate, these analogies. Sharp et al.’s suggestion that obvious and simple models are intuitively understood allowed us to employ simplification in design in the hopes of parsing down complex social media systems. Fig. 3 highlights this initial attempt where social media platforms became “networks” that formed proximity to specific groups or “nodes”. Fig. 3: Early version of the game board, with a representation of nodes and networks as simplified visualisations for social networks. This simplification process guided the scaling of design as we tried to make the seemingly boundless online networks accessible. Colourful tokens represented users, placed on the nodes (fig. 4). Tokens represented portions of the user base, allowing players to see the proliferation of conspiracy through the network. Unfortunately, this simplification ignores the individual acts of users and their ability to bypass these pipelines as well as the discovery-driven collegiality within these communities (Bloom and Moskalenko 57). To help offset this, we designed an overarching scenario and included “flavour text” on cards (fig. 5) which offered narrative vignettes that grounded player actions in dynamic story. Fig. 4: The first version for the printed playtest for the board, with the representation of “networks” formed by a clustering of "nodes". The movement of conspiracy was indicated by colour-coded tokens. Fig. 5: Playing cards. They reference a particular action which typically adds or removes token. They also reference a theory and offer text to narrativise the action. Design demonstrates that information transmission is not entirely static. In the most recent version (fig. 6), this meant having the connections between nodes become subverted through player actions. Game mechanics, such as playing cards (fig. 5), make these pipelines interactive and visible

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.