Introduction

Today, a social media user engages with an average of 6.6 social media platforms and spends on average 2 hours 24 min per day on these platforms [source]. It can be argued that such widespread use of social media is conditioning people into wanting ever more engaging experiences just to hold their attention. We see some evidence about this in the broader trends related to how people spend their leisure time:

Falling proportion of reading: The share of students who say they read for fun almost daily has secularly decreased across age groups from 1984 to 2020. Further, this trend is more pronounced in 13-year olds, where the proportion has halved from 35% to 17% [source].
Rapid growth of Video Games: Fortnite- launched less than 5 years ago- now has 350M+ users with 64% of users spending 6-21 hours/week [source]. Likewise, Roblox has grown from 9M+ (2016) to 200M+ (2021) with daily active users spending an average of 2.6 hours per day on the platform [source]. The platform is dominated by young users with 67% of users under the age of 16.
Rapid growth of TikTok: TikTok with its short form content and never-ending feed has become the 7th ranked social media app in 2021. In spite of being launched just ~5 years ago and its core feature being copied by Instagram, it has surpassed Twitter, Telegram, Reddit, Pinterest, and SnapChat has 1B+ monthly active users [source].

As social media and gaming companies competitively up the ante to avoid getting irrelevant, experiences are likely to get increasingly more gamified and immersive to capture user attention. Gamification, therefore, becomes one of the important tools to study while creating products for users conditioned to gamified environments.

Although gamification is not a new concept, new technologies bring in fresh affordances that make it possible to apply older techniques in novel ways. For example, VR headsets provide richer audio-visual ‘feedback’ as compared to other smart devices. This allows for the creation of new experiences such as Supernatural, which combines this feedback with workout-related physical movements to create fun exercise routines. Similarly, blockchain technology brings in fresh affordances that impact how gamification is implemented. For example, crypto tokens make it possible to offer ‘rewards’ in innovative ways that align the interests of different stakeholders. Likewise, ‘avatars’ can be minted as NFTs, which can be owned and traded. This has given rise to a new business model of ‘play-to-earn’ in gaming. We, therefore, aim to study the fundamentals of gamification and learn how to apply the same with new technologies.

Problem

Gamification could be used in various domains to achieve a variety of goals. It could be used to engender intrinsic motivation in individuals as well as to facilitate collective actions among large groups. For example, the Superhuman app uses game design principles to increase productivity by helping manage emails. On the other hand, Niantic uses game mechanics in Pokemon Go to build a 3D map of the world. For the purpose of this study, we focus on collective action problems in the context of online platforms and marketplaces. Broadly, we seek to better understand “how to apply gamification techniques to drive user-generated content on social media.”

We define social media as interactive technologies that facilitate the creation and sharing of information through virtual communities and networks. We note that social media algorithms are optimized for user engagement. This has resulted in negative externalities such as the spread of misinformation and the formation of echo chambers. On the flip side, platforms battling this problem through unilateral censorship lead one to question the neutrality of platforms [more]. We, therefore, explore whether we can use gamification to mitigate this problem of misinformation and echo chambers. Specifically, we want to find “whether we can counteract bad behavior and crowdsource better content using rewards in the form of crypto tokens.”

Scoping

We derive inspiration for a potential solution from casual gaming and live-streaming, two broad phenomena observed to drive engagement on social media.

Casual gaming is an important driver of growth both for social media platforms as well as gaming platforms. It is less demanding on the player as well as the game developer. Players can start engaging with the game with a little-to-no investment of money, time, and skill. Game developers, on the other hand, have less challenging technological constraints such as choosing between local vs remote processing, requiring GPUs, low latencies, etc. Furthermore, since there are few hardware-related constraints, casual games can be supported across platforms such as mobile, PCs, and consoles. Cross-platform interoperability, in turn, enables greater participation, resulting in a better social experience.

In this study, we focus on a sub-genre of games called Massive Interactive Live Events (MILEs) [more]. MILEs are a new genre made possible by cloud game streaming. They are distinct from most versions of cloud games in that there is not a distinct simulation or processing of a game for every user. In most cases, there will just be one simulation and every player (and there could be millions of them) is a co-equal participant. MILEs don’t necessarily need their gameplay to be processed in the cloud- individual, consumer-grade processing can be used. What matters is that the delivery occurs via streaming video. By avoiding the standard game model of myriad individual simulations (local or remote), a MILE need not synchronize simulations, only inputs.

In the subsequent sections, we explore the different aspects of gamification and understand how they work together to create a play-like experience. Next, we review existing literature related to collective action, gamification mechanisms, and streaming. We finally design a simple MILE and apply the gamification technique in a non-game context of our interest.

Background Research and Literature review

MDA Framework: To verbalize and understand the concept of gamification we delineate gaming elements into Mechanics, Dynamics, and Aesthetics using the MDA Framework [more]. In addition to the MDA elements, we classify certain game elements as Components [more]. We then classify commonly used game elements in the form of a table for easy reference.

Mechanics describes the particular components of the game, at the level of data representation and algorithms. Dynamics describes the run-time behavior of the mechanics acting on player inputs and each other’s outputs over time. Aesthetics describes the desirable emotional responses evoked in the player when they interact with the game system. Components describe game elements that can be seen and interacted with during the game.

Fundamental to the MDA framework is the idea that games are more like artifacts than media. In this framework, the content of a game is its behavior and not the media that streams out of it towards the player. Thinking about games as designed artifacts helps frame them as systems that build behavior via interaction [more].

To come up with a solution for our question “whether we can counteract bad behavior and crowdsource better content using rewards in the form of crypto tokens”, we research the following related areas: First, we review gamification-related literature in different contexts since we need to better understand the mechanics and process behind designing gamification. Second, we review literature related to collective action problems since our problem is related to user-generated content on social media. Lastly, we review literature related to live events and streaming since we are exploring the viability of a solution in the context of a MILE.

Intrinsic Motivation: Based on the review of existing literature, we find that points, badges, and leaderboards (PBL) are some of the most common game components used for gamification. However, blindly relying on the usage of PBL without considering the underlying motivation and user behavior has often failed to yield desired results [more].

Gamification at its core is about generating intrinsic motivation to engage a user in a certain behavior, X to achieve a certain goal, Y. Intrinsically motivated behavior likely results from motivational needs for competence, autonomy, and relatedness. Competence refers to feelings of mastering the challenge at hand. Autonomy refers to the freedom of choosing what challenges to undertake, and relatedness refers to experiences of recognition and acceptance [more]. To engender intrinsic motivation for a complex task, we may divide a larger whole into sub-tasks with clear goals and provide direct feedback for accomplishments, reframing an activity by establishing a meaningful narrative, or by gathering a social community to provide support. Core loops are an important mechanism for implementing just this.

A core loop is a series of repeated patterns related to the core behavior a user goes through while using the product. A simple core loop has three repeating steps 1) action, 2) reward, and 3) expansion. The user performs an action, is rewarded for it, and that reward helps them “expand” their growth or progression within the product. Between reward and expansion is “anticipation”, which is when the brain releases dopamine to the user. This is a huge part of what causes motivation, and “addiction” for lack of a better word. Over repeated loops of anticipation and expansion, we begin to see “investment” into the product— which creates a sense of dedication and reduces the chances of the user leaving the product [source].

Similarly, variable rewards are known to influence human behavior and have been used widely in games. Variation in reward could be introduced in terms of both quantity as well as time interval. To create a meaningful gamification experience within a product, we must craft an engaging core loop consisting of two separate session loops- inner loops and outer loops- combined with some form of variable rewards. Minor rewards must be mapped to inner loops, and major rewards must be mapped to outer loops, with some degree of randomness. Doing so ensures users are more inclined to complete inner loops over and over again for the anticipation of receiving their desired major reward [source].

We observe this phenomenon in fitness products that gamify working out to create fun experiences. People work out for minor rewards such as likes, badges, and leaderboard-related achievements. Positive recognition, reciprocity, and social influence have a positive impact on how much people are willing to exercise as well as their attitudes and willingness to use gamification services. Moreover, the more friends a user has in the service, the larger are these effects [more].

Collective Action: The design of appropriate incentive mechanisms that get people to participate in crowdsourcing and invite others via word of mouth is of great relevance for the designers of crowdsourcing initiatives. Studies have shown that extrinsic incentives, such as financial compensations or utilitarian benefits that arise from the purpose of a crowdsourcing initiative, often play a subordinate role in crowdsourcees’ motivations. Various studies indicate that crowdsourcees are driven by intrinsic aspects, such as altruism, the sense of accomplishment, self-development, curiosity, competence satisfaction, or relatedness with a community of peers [more]. Competition and cooperation are, therefore, important game mechanics when it comes to mobilizing collective action. We find that for crowdsourcing applications, combining both the mechanics yields the best result [more].

Inter-team competitions are most likely to lead to higher enjoyment and crowdsourcing participation, as well as to a higher willingness to recommend a system. Crowdsourcing system designers and operators should, therefore, implement gamification with competing teams instead of typically used competitions between individuals. Studies also indicate that motivational and behavioral outcomes of gamification features, such as leaderboards can differ according to the specific design of a gamification feature. Lastly, there was no significant difference between the gamification conditions concerning the perceived usefulness of the system. In other words, gamification does not in and of itself improve the utility of the system.

We also find that cooperative game features and the mediating group dynamics are a powerful set of predictors for people willing to work together. To design cooperative games we can utilize three key design features: (1) cooperative games apply goal structures that give one reason to cooperate, (2) cooperative games provide special rules and mechanics that enable and support cooperative behavior, & (3) cooperative games provide communication features to allow social interaction [more].

Streaming: Communication style (community-focused communication or content-focused communication) has varied impact on monetary and non-monetary outcomes. Depending on their communication focus, streamers should choose between adopting a utilitarian-superior style or a hedonically superior style. The utilitarian-superior style should be particularly embraced by streamers when they center their communication on the content to drive monetary outcomes as it can further enhance it. Nevertheless, it should be neglected when the streamer follows a community-focused approach, because it amplifies the negative impact on financial consequences of a stream [more].

Designing the artifact

Applying the MDA framework, we characterise social media as games or artifacts rather than media. Put differently, the content of social media artifact is its ‘engagement behavior’ and not the media that streams out of it towards users. We, therefore, attempt to design an artifact as a solution to the problem of our interest viz. “whether we can counteract bad behavior and crowdsource better content using rewards in the form of crypto tokens.” We do this in the context of live streaming events such as news broadcasting, podcasting, etc. Specifically, we seek to crowdsource quality content from viewers to enrich the live content.

We note that the social media algorithms are optimized for user engagement [more]. In the gamification parlance, the algorithm surfaces content that is clickbaity to a given user. The clickbaity nature of the content could be due to the user’s genuine interest, misinformation or exaggeration, or inherent biases of the user. In any case, the clickbaity content gets ranked higher by the algorithm. This, in turn, drives further engagement, thereby reinforcing the content selection loop. To fight this problem, two types of solutions have been discussed [more]:

• “final ranking providers”: third parties who take pre-digested feature vectors from the underlying content platform, then use these to do the final ranking of items in whatever way they want.
• “constraint providers”: third parties who provide constraints in the form of computational contracts that are inserted into the machine learning loop of the automated content selection (ACS) system.

Both these solutions propose working with proprietary algorithms- either borrowing pre-digested feature vectors or directly interfacing with the machine learning loops of ACS. Since there’s no incentive for social media companies to cooperate and fix the negative externalities, we explore a solution that directly deals with user-generated data (such as tweets, posts, etc). To fight the negative externalities of social media, we propose using rewards in the form of crypto tokens to help surface ‘good’ content. In other words, we propose using one form of gamification mechanism (i.e. crypto rewards) to counteract the negative effects of another form of gamification mechanism (i.e. content loops). We propose doing this by designing a contest in the form of a MILE that complements the live stream of a content creator.

Goal: Tackle echo chambers by exposing people to diverse perspectives at a MILE

Contest Rules:

• Only 3 argument categories are allowed (For, Against, & Reframe)
• No cap on the no. of arguments that can be submitted by a Player
• Every submission requires Players to wager News Tokens (NTs)
• Cost of wagering a submission increases with time
• Viewers can participate as Supporters by backing Players with NTs
• Winning statements get decided by vote (1 person = 1 vote)
• 3 winning statements chosen by vote: 1 per category.
• Winnings are shared equally among 3 categories
• Voting results are displayed only at the end

Rules for Sharing the Earnings:

• 4 stakeholders: Developer: Content Creator: Players: Supporters
• The pot will be distributed in the following way:

  • Developer: 10%,

  • Content Creators: 15%.

  • Players: 15% (5% for each category), and

  • Supporters: 60% (20% for each category) Earnings in proportion to the wager amount.

Limitations and Future Questions:

Gamification applications are complex information systems. They require holistic information system design, taking into account not only the technical aspects but also the multidimensional aspects of user psychology and engagement. Gamification design, therefore, needs an iterative, user-centered design process with a high degree of user involvement as well as early testing of design ideas [more]. Our attempt is, therefore, limited in that regard since it has not gone through rigorous user testing.

Further, research suggests gamification cannot give something to people that they do not want. In that sense, it’s more of an amplifier for something that people already want. ACS algorithms that are optimised for engagement seem to suggest users want content that leads to echo chambers. So, the central question of our hypothesis is: Would users want a gamified experience with crypto tokens more than echo chambers?

Other Questions:

1. Rewards
   1. What should token economics be like for the rewards to be effective?
   2. Would users want vanilla financial rewards over crypto tokens?
2. Motivation
   1. How do we sustain the crowdsourced activity?
   2. How do we balance intrinsic and extrinsic motivations for such an artifact?
   3. How can the artifact or the game be modified? Should we use elements of chance such as variability in rewards?
3. Trust & Safety
   1. Can a group coordinate and pool resources to subvert the game?
   2. How can we prevent ‘bad’ actors/ideas from gaining legitimacy due to association?

Appendix