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Many of the problems associated with making an MMO, a Massively Multiplayer Online game, come in large part from the very first term: “Massively”. An MMO is notably tricky to build due to technical issues involving server scaling, as well as design issues involving scaling economics, politics, level design, pacing, persistence, and progression. A rule of thumb is that development costs grow exponentially as the number of players increases, but for many years, there’s been an unquestioned assumption that bigger player numbers are inherently better and therefore worth pursuing. Yet we see clear counterexamples. Many early MUDs (Multi-User Dungeons) involved populations of dozens-to-thousands of people and still have vibrant communities to this day [1]. Multiplayer Minecraft is wildly successful, despite its reliance on relatively small, instanced servers. And many modern hit games, like Fortnite, are online games that successfully limit their focus to matches of 100 or less. What are the critical design lessons from these smaller online games—and how can current research and understanding of social psychology help make sense of those lessons? We combined our decades of experience designing social systems for online games and a deep dive into current academic research to arrive at a set of best practices and common pitfalls. What we’ll cover in this paper:
When researching what it meant to make human-scale systems, we found several key concepts from social psychology. Each provides a set of constraints for social design. Social game design operates within the physical and mental constraints of the human animal, so it pays to understand these constraints and build them into our designs. A friendship is a single social bond between two people. Friendship formation is a distinct process involving proximity, similarity, reciprocity, and disclosure. An individual has a highly structured distribution of relationship bonds. People tend to have a maximum of 150 total friendships [2], including 50 good friendships, which include 15 best friendships, which, in turn, include 5 intimate friendships. This web of relationships can be modeled as an egocentric network with the individual at the center. This paper focuses primarily on the implications of Dunbar’s Layers for human-scale social design in online games. A social group of is a collection of people brought together for a shared task or interest. Groups contain multiple overlapping individual networks. The performance of the group, as a whole, is dependent on how the friendship bonds across the entire group are leveraged to accomplish the shared activity. At the most basic level, human-scale game design is about creating strong relationship bonds between individuals. Most game populations will start out with weakly-bonded individuals. You’ll need to create activities, incentives, spaces, and social structures that actively build friendship in order to enable even the most basic of trust-based activities. This section is a brief overview. For more detailed discussion on this topic see the 2016 Project Horseshoe paper on game design for building friendships. Friendship formation requires 4 key ingredients:
You can take any two players, put them together in matches for hundreds of hours, and if the above criteria are not met, they are unlikely to become friends. Naively tossing bodies at one another is not efficient social design. As a designer, you specifically have to build opportunities for consensual reciprocity into your game loops. These look like the following:
Common Variations
Friendship is a long-term process. Each reciprocation loop may take seconds initially, but you need thousands of linked loops to build a robust friendship.
For example, friendships in an MMO tend to start out with parallel play, where two people simply see one another’s name while fighting monsters in the same area. This then escalates to helping one another; a heal spell, an emote of celebration, a dropped item. The two players may start chatting in order to take down harder monsters; they may also friend one another and start talking more about who they are and what they are interested in. At each stage, interactions take increasing time and effort. And involve richer communication. Each micro-loop is not very expensive, but over long-term repetition of many such loops, the relationship accumulates meaningful amounts of trust. Design these systems with the same rigor, care, and eye for economic balance that you’d put towards a combat or progression system. Almost every stage of these reciprocation loops involves consent. Each party must consent to both starting, continuing, and escalating the relationship. At any point, it is totally fine for one or both parties to pull away, either to slow down or move onto some other relationship opportunity. In the context of Dunbar’s Layers, there’s a limit on the number of people an individual can have in their lives. The process of building friendship is also the active process of curating relationships that are healthy and mutually satisfying. When players actively and enthusiastically consent to engage in your reciprocation loops, you’ll find that the relationships you build in your game are more authentic, last longer, and ultimately provide more value to your players. An individual organizes their friendships by strength of their one-to-one bonds. They have close friends they turn to in times of crisis and more casual friends, with whom they interact with less frequently. Social psychology has been studying these friendship networks for decades. One of the more reproducible findings is the existence of strong limits on the number and strength of bonds an individual can have with other humans. Robin Dunbar is an anthropologist who, in the 1980s, posited that a human can have up to 150 meaningful relationships, based off his investigations into primate social brain structures [3]. When others attempted to verify this prediction, they found that “Dunbar’s Number” kept coming up in long-lasting groups in the real world. It’s been replicated across a huge number of domains including businesses, religious organizations, military groups, and, of course, MMO guilds. However, as researchers dug further into the data, they noticed additional stable clustering at lower numbers of connections. These smaller clusters were part of a person’s total of 150 relationships, but involved much stronger bonds.
Visualization of Dunbar’s Layers. Each block represents time to build one relationship in that layer. Dunbar’s Layers, as these smaller clusters are known, are generally organized as follows:
Note that each layer is cumulative and contains the previous layers, so your best friend layer contains your intimate friends layer as well. A common confusion is to think you have 5 intimate friends AND an additional 15 best friends, etc., but those 5 intimate friends are part of your 15 best friends budget. These numbers are averages and, in reality, describe tight ranges. In practice, different people have different degrees of social needs and relationship-building capacity. For example, many men average 3-4 relationships that they would consider intimate friends or family, while many women average 7-9 such relationships. Some people, known as “super-connectors,” have upward of 200–250 meaningful friendships. With larger data sets, we’ve discovered these relationships layers also extend past actual friends.
On first glance, Dunbar’s Layers are a mere curiosity. However, they fundamentally shape how people socialize. The following are aspects of Dunbar’s Layers worth knowing about before you attempt to use them in a design.
Visualizing the innermost Dunbar’s Layers as an egocentric network. Note all connections are from the perspective of a single individual. An ideal way to visualize Dunbar’s Layers is as a network of connections, not as separate layers, per se. In research, this is known as an “egocentric network.”
There are several different ways egocentric networks can be used in analysis of individual relationships:
Overall, having a deep friend network has an immensely positive impact on your health and happiness.
On the flip side, toxic relationships have an outsized negative impact on mental and physical health. Something to think about when we deal with trolls in our games [9]. Building friendships takes many hours of interaction. The time required to build a single friendship bond [10]:
If you meet with someone for 1 hour each week, it will take roughly a year before you consider one another even casual friends. Friendship formation is not a cheap activity. Maintaining relationships takes less effort. Three key variables here are kinship, gender and frequency of interaction. Kin bonds (bonds with family members) require less maintenance than non-family friendship bonds and do not seem affected by distance. Men tend to affirm bonds by participating in activities together, while women tend to talk with another. Higher strength bonds needs more frequent renewal than lower strength bonds.
One way of thinking about the constraints suggested by Dunbar’s Layers is to imagine you have a budget of cognitive resources that can be spent on relationships. The physical limits of your human brain mean that you only have enough mental budget for a total of roughly 150 relationships. Humans have developed a few tools that have expanded our ability to organize into groups well past our primate cousins—most notably language—but also large-scale systems of government and economics. In the early 2000s, people assumed that new technologies like online social networks could help break past Dunbar’s Number; by offloading the cost of remembering our friendships to a computer, we could live richer, more social lives, with strong relationships to even more people. We now have copious data that this is not the case. Studies suggest that there’s still a limited budget of cognitive resources at play and even in online platforms we see the exact same distribution of relationships [11]. If anything, social networks damage our relationships. By making it possible for us to cheaply form superficial relationships (and invest our limited energy in maintaining them), such systems divert cognitive resources from smaller, intimate groups out towards larger, less-intimate groups. The result is that key relationships with best friends and loved ones suffer. And, unfortunately, it is the strength of these high-trust relationships that are most predictive of mental health and overall happiness [12]. A social group is a set of individuals labeled as being in a group. This is inherently a fuzzy concept, since the true structure thereof is an overlapping network of egocentric networks, partially-negotiated social norms, and ever-shifting relationship bonds. There are three dominant perspectives on what makes a group. Social Identity perspective: “I feel like I’m part of a group.” An individual can self-identify if they are part of a group. By doing so, they start practicing the social norms of the identified group. This is the perspective that gives birth to either imposter syndrome or a feeling of belonging. Self-categorization perspective: “I feel like you are part of a group.” Someone looking at the behavior of other people can identify if others are behaving as part of a group. By doing so, they treat those people as if they operate using shared social norms. This is the perspective that gives birth to stereotypes. Social cohesion perspective: “We act according to shared social norms.” A set of people that act in similar manner across a variety of social variables is a group. Those variables include:
Additional factors that can be used to determine group cohesion include:
The social cohesion perspective proves the most design insight, so we’ll be referencing it for the rest of this discussion. Common groups sizes roughly align with Dunbar’s Layers. However, these are not identical concepts. Social groups can contain friends of varying trust levels. You could have a small group composed entirely of strangers. whereas a 5-person intimate friends layer is, by definition, an individual’s closest set of friends. These are some of the most common task-oriented groups to form. Non-kin, task-focused groups of these sizes often dissipate when the task is complete. Small groups are, however, able to attain the highest strength of social bonds, usually focused on key family relationships.
These are the largest-possible friend groups. Example groups at these sizes include a guild, shard, or map in an MMO, a mid-sized company, or a social organization in a university.
These larger groups are composed of smaller friend-based sub-groups. However, due to their size being larger than Dunbar’s Number, it is impossible for them to engage in very high-trust activities without additional systems like hierarchy, reliance on weak ties, or codified rules.
Group trust, much like friendship, forms according to a process that imposes constraints on any social design. When we matchmake a set of random players together, we first get a low-intimacy, low-trust group of strangers. We then need to take that group through a period of social norm formation and relationship building. This process creates a rich, highly predictive social contract between individuals, which enables people to depend on one another in dynamic group activities. Tuckman’s classic stages of group formation are:
This relates to Dunbar’s Layers in a few key ways:
Groups vary substantially in how long they last. There are two distinct types of groups worth looking for when designing your group systems:
Even through group size and Dunbar’s Layers are very different concepts, they do seem to be related. Small groups are stable at around 5 people, primarily due to their heavily reliance on long-lasting family relationships. Large group sizes tend to stabilize around the 50, 150, 500, and 1500 values found in Dunbar’s Layers. This works in two directions:
Groups at 50 and 150 find long term stability, often measured in years, by benefiting from peer pressure (norm reward and censure), without the need for complex rules and hierarchy. The stronger the sense of shared purpose, the more robust the group. There’s more research to be done here, but this seems to be the maximum group size where, due to the limits of Dunbar’s Layers, you can rely on unaugmented human nature to self-organize into stable groups. Stable groups at 500 and 1500 are far rarer because they require the addition of some from of hierarchy in order to be sustainable. Usually this involves appointing a small group of 4-5 decision makers who represent other 50 to 150 member sub-groups. These decision makers represent ‘weak ties’ between groups. Weak ties are key to the stability of 500 and 1500 player groups. They let a group of 50-150 reach out to other groups and quickly gain access to resources, opportunities, and information. Studies show having a diverse set of weak ties -- particularly in a large community of uncaring strangers -- increases life satisfaction. Weak ties are not universally good for game developers.
If anything, modern MMOs suffer from too many weak ties and not enough emphasis on building and supporting strong ties. Perhaps because MUDs and early online games were historically rich with strong bonds, MMO designers simply assumed they’d get those for free. They didn’t realize their desire to build a big game—which historically has been conflated with popularity—was antithetical to the magical social connections that made early online games attractive in the first place. Shared goals are the single strongest predictor of group cohesion. Groups with more group pride and stronger task commitment have strong shared goals. They are most likely to perform well at high-trust tasks, and have high retention, longevity, and increased sense of member well-being. Members with strong group pride feel strong allegiance to the group, are happy with what the group accomplishes, and promote the group identity to others. Group pride is expressed in the same fashion across different group sizes, but identity becomes more formalized as group size increases.
Task commitment is about shared activities that contribute to a common goal. Group pride answers, “Who are we and do I belong?” Task commitment, by contrast, answers, “What are we accomplishing by working together?”
Every group needs to agree on roles within society. These are composed of appropriate division of labor and division of resources. Specialization increases with group size.
Economic complexity increases with group size.
Status and hierarchy start out relatively undefined in smaller groups and grow in complexity with group size. Leaders become more important and less personal in larger groups.
Hierarchy becomes increasingly necessary as group size increases.
Norm formation in social groups involves how a group determines the rules they operate by and how they communicate those rules. Rule formation becomes increasingly formalized as group size increases.
Communication shifts from reciprocation loops to broadcast as group size increases.
What happens when norms are violated?
Considering the constraints imposed by friendships, Dunbar’s Layers, and social groups, it is worth exploring game design that is centered around natural human social scales. Human-scale design is social design that targets the 5, 15, 50 and 150 person egocentric networks and associated groups. It explicitly avoids player systems involving 500 or more players. If you can build a human-scale game that enables a player to spend quality time with good friends, you’ll likely improve the quality of their life. While if you break these hard limits, you actively damage your game’s social systems. These social psychology models should do more than just inform our evaluation of game systems—they should be actively shaping the way we approach design. Such an approach focuses on smaller, more intimate social design as the core of a game. It is less concerned with big numbers and infinitely scalable systems, and more interested in fostering trust and connection between players. This perspective led us to some fundamental insights concerning how we approach online game design. A common pattern when designing an MMO is:
As a result, the final systems are often surprisingly complex. You’ve jumped directly into designing systems that need to handle the many issues associated with 500+ groups (i.e., your player population). Immediately, you are faced with the key problem that your world is just a large, empty area where a player sporadically meets strangers they don’t trust. As conflict inevitably arises from these low-trust interactions, the dev team toils to add a vast amount of bureaucracy to manage the poor player experience. It can feel like patching unending leaks in a poorly-placed dam. In the best cases, like EVE Online, players create their own systems of crude governance to shore up the faulty social design. But for the majority of games, we see outcomes like The Sims Online, where mob-style groups grief new players and chase them from the game. From a social design perspective, this process sets the team up with the hardest possible design challenges, essentially creating a lot of extra problems that then need to be solved. Focusing on designing for human-scale suggests a different approach:
This approach has the advantage of more closely mapping to how humans have grouped historically: in nested layers of families, tribes, villages, etc. Sticking closer to the natural shape of social grouping will make your group activities feel more familiar and facilitate social bonding. It will also allow you to apply lessons and best practices from psychology and anthropology more directly. When game designers think of retention, we often first consider User Experience (UX). Using the logic of UX, if a developer builds a complicated core interaction that is difficult for a player to understand, most players will churn out early on. Such games should have poor early retention and struggle with new player acquisition. However, the game industry has many counterexamples. Dwarf Fortress, Go Pets, and Dofus are three games renowned for their poor user experiences. They have weak tutorials, byzantine gameplay loops, and a general lack of traditional first-time user experience polish. By all traditional UX values, they should be failures, yet they are not. While these games have poor UX, they also have strong social design. For example, Dofus is a game that is specifically popular in France. Its developers tried to expand its reach to other countries with limited success, for many of the aforementioned reasons. What made France special for Dofus?
This was not intentional, but the result was that Dofus ended up being played predominantly by friends, many of whom were already part of each others’ 50, 15, and 5 person layers. This allowed players to build groups stocked up with high-trust compatriots and overcome the high-trust activities in the game. Succeeding at those challenging activities in groups of trusted friends gave the game incredibly high engagement. A virtuous cycle occurs where strongly-bonded friends make a game their homebase—a safe, intimate space for acting out their friendship. In turn, those players recruit more of their friend networks into the game. We’ve observed a similar process in other poor-UX, high-retention game examples. To be clear—poor UX is not the root driver for these games’ avid, high-trust communities. Instead, it is one of many pragmatic reasons for players to bring the inner circles of their friend networks into a game. The reverse of the same basic process that drove the success of Dofus highlights problems with early Facebook-style virality. Such “social network games” would obsessively incentivize players to send out invites to as many people as possible. Two results occurred:
All of these examples highlight the basic truth that social design is deeply powerful, but is often not a first-order consideration for designers. A very common confusion that came up many times during our discussions was the difference between friends, Dunbar’s Layers, group size, and concurrency (the number of players simultaneously logged in). These are all four distinctly different concepts, yet it is common for social designers to use them interchangeably. Much of this is the fault of our existing terminology. When we talk about multiplayer games, a common shorthand is to say, “It’s a 16-player game.” We all know that this means there are 16 concurrent players in a match or room, but we often erroneously assume that this also means they are all friends and/or that they are all part of the same social group. Both of these errors are a naive misunderstanding.
In general, having 16 people online together says almost nothing about whether or not they are in a group, or what the strength of their relationships might be. It is tempting to fall back on old, inexact language, but your game will suffer. Instead, teach your design teams about friendship formation, constraints on types of friendship, trade-offs involved at different groups sizes, and the logistics of social play. The structure of Dunbar’s Layers gives us insight into how many friends of a given trust level you can expect a player to have online at any particular time. There are logistical implications for matchmaking, events, and more. At the most basic level, the logistics of Dunbar’s Layers help you predict the outcome of the following example:
However, we can gain more detailed insights. Here’s how you calculate the exact portion of a player’s friend graph you can actually address with your game. First, you’ll need a few pieces of information:
Share of Social Time is the percentage of a player’s total time spent socializing that is spent inside your game. This corresponds roughly to the percentage of a player’s social graph that is active in the game.[13] If a player spends 50% of their social time in a game, we’d expect roughly 50% of their friend network is also in the game.
There are a couple ways of calculating this. Conservatively, we know from time-usage studies that the average American has approximately 5 hours of leisure time per day [14]. From this perspective, Share of Social Time equals Hours per Day Spent In Game / 5 hours. However, less conservatively, we know that people tend to spend approximately 0.65 hours per day actually socializing. This is likely an underestimate since the time-usage studies don’t measure time spent socializing at work. Nor do they consider time spent in playing games [15] as socializing. For the following calculations, we’ll use the conservative definition of Share of Social Time. For comparison, the heaviest players of Fortnite, around 8% of the player population, spend 3+ hours playing per day. That’s roughly 60% (or more) of an average American’s total leisure time. Concurrency ratio is the ratio of monthly active players (MAU) to those currently online. Since synchronous activities require people to be present, it does us no good if you have friends in a game, but they aren’t actually playing. A highly-social MMO will have a concurrency ratio of 10:1, so for every 10 MAU you’ll have 1 of those players online. An international phenomenon like Fortnite enjoys a 20:1 ratio, while many web-games are as low as 150:1 or 250:1. Dunbar’s Layers suggests that our relationships map onto a very specific frequency distribution of friends.
Chart 1: Percentage of friend network layers present in the game This distribution holds true only if we make several assumptions:
We can use Share of Social Time, Concurrency, and distribution of friends to calculate some useful information about our game. Let’s say you have a highly engaging MMO:
How many friends will be in the player’s friend list? Given the standard distribution of friends, 50% of that player’s social network will be present in your game. With a total of 150 friends that means there will be 75 friends playing the game. How many friends will be online right now? Of those 75 friends in the game, due to the concurrency ratio, only 10% (7.5 friends) will be on at any point in time, on average. What type of friends will be online right now? Using the distribution of friends in various layers from the chart above and multiplying them by the total friends online, we can expect the following distribution of friends:
This sort of calculation puts much harder constraints on the types of activities that we can build into our game. Note that this is a best-case scenario. A highly-social MMO with great concurrency, and a player with a fully-engaged friend network. In this best-case situation you are lucky to get a single good friend playing alongside you. You will however get a few casual friends. This suggests that the core activity of even highly-social games with long-term, highly-invested players should predominantly be target low-to-moderate trust activities involving 5-7 players. What does this distribution look like at different cohort sizes? Using the same logic, you can see what friend distributions would look like at various fixed populations of active players.
Chart 2: Max and Average number of friends an individual will have for various cohort sizes in a game with 50% share of social time and 10:1 concurrency. Due to the logistics of concurrency ratios and Share of Social Time, we max out the number of friends online at around 1500 people in a cohort. Simply having bigger cohorts doesn’t improve friend concurrency. The previous calculations are just an average of the sort of friends you can expect online. By shiftings a few variables around, we can create much higher densities of friends.
By translating fuzzy social psychology concepts into more mechanical concepts, we can start treating social design as a form of systems design. (Some may find the term 'social systems design' more palatable than 'social game design' after dealing with the horrors of Facebook.) In particular, social design benefits from using the internal economy perspective, where relationships are modeled as resources and transformations on those resources.
Dunbar’s Layers act as a cap on the maximum number of each level of relationship you might have. When a relationship pool fills up in one of the outer layers, it may transform into a new pool in one of the inner layers. However if the inner layers are full, one must give. If any of the layers are empty, the player seeks actions that fill them. This paints the process as rather cold and transactional. In practice, this type of design drives intense emotions. Losses of social capital yield strong negative emotions, while gains generate positive emotions. Rate of lose or gain will dramatically intensify the emotional response. If your goal is to make players laugh, cry, or otherwise experience the peak of what it means to be human, build strong social systems. When we develop a game that involves group sizes of 500 and 1500 people, we’ve created populations beyond the human brain’s ability to understand other people through personal relationships. Our players know nothing about most other individuals, as they are incapable of building a large-enough social network to understand the whole. Instead, they must rely heavily on rules and heuristics to govern their interactions, and we, as game designers, are on on the hook to provide those structures. By simply upping the size of our community, we’ve introduced an immense design challenge. We now need to build systems to manage crime, corruption, economic complexity, classism, racism, and more. Suddenly, our games exhibit most of the ills of modern society and the burden is fully upon us to solve them. If we don’t conscientiously address these issues, our community collapses into a hellish online dystopia. If you care about maximizing social impact while minimizing scope:
Games that thrive are almost always ones that satisfy a strong audience motivation. This is no different for social games and social features. Dunbar’s Layers, in particular, give us a structure for understanding the player’s social motivations. “The belongingness hypothesis proposes two main features. First, people need constant, positive, personal interactions with other people. Second, people need to know that their bond is stable, there is mutual concern, and that this attachment will continue.” You can think of the various relationship layers as a slots in a list. Everyone has space for about 5 intimate friends, 10 best friends, 35 goods friends and 100 casual friends. If those slots are filled with healthy, mutually-beneficial relationships, a person is reasonably happy. However if any of those slots are empty, people have a strong desire to fill them in. When they don’t have those slots filled they tend to be unhappy, and, in response, will seek the company of others using several key strategies:
Life events are predictive of gaps in a person’s friendship network. As new people show up in a person’s life, there’s less time for activities that require making new friends.
What loneliness looks like in a thinned-out network There are also numerous events that thin out a person’s network.
In particular, there seem to be three major periods in which loneliness spikes: Late 20s, mid 50s and late 80s. During these times one study reported as many as 75% of people report being lonely. These values hold across genders. Providing these individuals with tools for building healthy relationships would be immensely beneficial to society. All of this suggests opportunities for social game design to improve the lives of our players.
Both opportunities could be served by the same game, but be sure to sort incoming players based on their needs and direct them into activities that satisfy those identified needs. Key discoveries in social psychology place hard limits on the types of social games we can build.
These are the physics that social designers must understand and build into their designs. Many past designs ignored Dunbar’s Layers and naively assumed “more is better.” They ignore friendship formation and assume “it just happens.” They ignore social groups and arbitrarily mash players together. In reality, these assumptions are actively harmful and cause the following:
If players have not filled all the slots in their primary friend network, they suffer. And, in response, they are intrinsically motivated to deepen their existing relationships or build relationships with new people. Striving for belongingness is one of the strongest human motivations. They will naturally seek out activities that help them make friends and belong to something bigger than themselves. If your games help build relationships for the player in any of their inner layers, you’ll accomplish a couple key benefits:
If we take all the insights gleaned from research into group psychology, examples from online game design, examination of Dunbar’s Layers and social motivation—all of it into consideration, we can arrive at several, strong best practices:
As ethical game designers, we should strive towards some higher purpose beyond merely extracting money, time, and energy from our players. Building friendships and providing lonely people with human connections are goals worthy of our highest-quality work. If you are working on a multiplayer game, ask yourself how your designs help build social capital with and among your players. If you encounter people who believe that “more is better” when it comes to building social systems, we recommend you send them this report. There’s a new wave of social game design inspired by lessons from social psychology and we are immensely excited to be part of it. [1] Active MUD communities. Examples include, as of the time of this writing (December, 2018): Achaea, Dreams of Divine Lands (1997-present); Aardwolf MUD (1996-present); GemStone IV (1988-present); Realms of Despair (1994-present); and Threshold RPG (1996-present) [2] Dunbar’s Layers. “Generally speaking, humans each have one to two special friends, five intimate friends, 15 best friends, 50 good friends, 150 “just” friends and 500 acquaintances. Our relationships form a series of expanding circles of increasing size and decreasing intensity and quality of the relationship.” Woodward A (2017) With a Little Help from My Friends. Scientific American. Retrieved December 27, 2018, from https://www.scientificamerican.com/article/with-a-little-help-from-my-friends/ [3] Dunbar’s Number. “The figure of 150 seems to represent the maximum number of individuals with whom we can have a genuinely social relationship, the kind of relationship that goes with knowing who they are and how they relate to us. Putting it another way, it’s the number of people you would not feel embarrassed about joining uninvited for a drink if you happened to bump into them in a bar.” Dunbar R (1998) Of Brains and Groups and Evolution. In Grooming, Gossip, and the Evolution of Language (pp. 80-105). Retrieved December 26, 2018, from https://books.google.com/books?id=nN5DFNT-6ToC&pg=PA77 [4] The 50 Person Layer. “Thus, 50 individuals may represent a natural social grouping (in the world of personal social networks, it is the set of individuals that provides the bulk of one’s regular social contacts and all of one’s emotional and economic support…)” Kordsmeyer T, Carron P, Dunbar R (2017) Sizes of Permanent Campsite Communities Reflect Constraints on Natural Human Communities. Current Anthropology, 58(2), 289-294. Retrieved December 26, 2018, from https://www.psych.uni-goettingen.de/de/biopers/publications_department/ [5] Unequal dyadic bonds. “When analyzing self-reported relationship surveys from several experiments, we find that the vast majority of friendships are expected to be reciprocal, while in reality, only about half of them are indeed reciprocal.” Almaatouq A, Radaelli L, Pentland A, Shmueli E (2016) Are You Your Friends’ Friend? Poor Perception of Friendship Ties Limits the Ability to Promote Behavioral Change. PLoS ONE 11(3): e0151588. https://doi.org/10.1371/journal.pone.0151588 [6] Loneliness impacts longevity. “...individuals with adequate social relationships have a 50% greater likelihood of survival compared to those with poor or insufficient social relationships. The magnitude of this effect is comparable with quitting smoking and it exceeds many well-known risk factors for mortality (e.g., obesity, physical inactivity).” Holt-Lunstad J, Smith T, Layton J (2010) Social Relationships and Mortality Risk: A Meta-analytic Review. PLoS Med 7(7): e1000316. https://doi.org/10.1371/journal.pmed.1000316 [7] Friendship impacts life satisfaction. “...the results indicate that both having/meeting friends and good-quality friendship relations are important to an overall life satisfaction.” Amati V, Meggiolaro S, Rivellini G, Zaccarin S (2018) Social relations and life satisfaction: the role of friends. Genus, 74(1), 7. https://doi.org/10.1186/s41118-018-0032-z [8] Friendship reduces depression. “People who have close friends and confidants, friendly neighbors and supportive co-workers are less likely to experience sadness, loneliness, low self-esteem and problems with eating and sleeping. Indeed, a common finding from research on the correlates of life satisfaction is that subjective well-being is best predicted by the breadth and depth of one’s social connections.” Helliwell J, Putnam R (2004) The social context of well-being. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 359(1449). https://doi.org/10.1098/rstb.2004.1522 [9] Toxic relationships impact health. “...individuals who experienced negative aspects of close relationships had a higher risk of incident coronary events….” De Vogli R, Chandola T, Marmot M (2007) Negative Aspects of Close Relationships and Heart Disease. Arch Intern Med, 167(18), 1951–1957. https://doi.org/10.1001/archinte.167.18.1951 [10] Friendships cost time to build. For more details, see: Hellman, R (2018) How to make friends? Study reveals time it takes. KU News Service. Retrieved December 19, 2018, from https://news.ku.edu/2018/03/06/study-reveals-number-hours-it-takes-make-friend [11] Social media doesn’t expand our friendship capacity. “The fact that social networks remain about the same size despite the communication opportunities provided by social media suggests that the constraints that limit face-to-face networks are not fully circumvented by online environments. Instead, it seems that online social networks remain subject to the same cognitive demands of maintaining relationships that limit offline friendships.” Dunbar R (2016) Do online social media cut through the constraints that limit the size of offline social networks? Royal Society Open Science, 3(1). https://doi.org/10.1098/rsos.150292 [12] Intimate relationships best predict health. “...the presence of an intimate relationship (as opposed to a broader social network) [has] the greatest effect on explaining variance in depressed mood.” Roberts S, Arrow H, Gowlett J, Lehmann J, Dunbar R (2014) Close Social Relationships: An Evolutionary Perspective. In R Dunbar, C Gamble, J Gowlett (Eds.), Lucy to Language: The Benchmark Papers (pp. 151-180). Oxford: Oxford University Press. [13] How investment shapes social graph distribution. “the strength of a tie is a (probably linear) combination of the amount of time, the emotional intensity, the intimacy (mutual confiding) and the reciprocal services which characterize the tie” Granovetter M (1973) The Strength of Weak Ties. American Journal of Sociology, 78(6), 1360-1380. Retrieved December 28, 2018 from https://www.jstor.org/stable/2776392 [14] Available leisure time. The average American woman spends roughly five hours per day on leisure activities (35 hours per week), while the average American man spends about 5.5 hours per day (38.5 hours per week). Bureau of Labor Statistics, U.S. Department of Labor (2018) American Time Use Survey — 2017 Results. Press Release for the Bureau of Labor Statistics. Retrieved December 20, 2018, from https://www.bls.gov/news.release/pdf/atus.pdf [15] Why are people socializing in games? “On the face of it, this may seem like a sad state of affairs. It could even be read as dystopian: people are escaping real life to be in virtual worlds. People often find community within gaming worlds, and may get a heightened sense of shared experience from competing against or teaming up with people across the world who share their interests. In some cases, these connections might even be more valuable than, say, gossiping with a neighbor.” Kopf D (2018) Americans are socializing less and playing more games. Quartz. Retrieved December 28, 2018, from https://qz.com/1320344/americans-are-socializing-less-and-playing-more-games/ Bura S (2008) Emotion Engineering in Videogames. Retrieved December 28, 2018, from http://www.stephanebura.com/emotion/ Casari M, Tagliapietra C (2018) Group size in social-ecological systems. Proceedings of the National Academy of Sciences, 115(11), 2728-2733. https://doi.org/10.1073/pnas.1713496115 Cook D, (2018) Game design patterns for building friendship. GDC 2018. Retrieved December 28, 2018, from https://www.youtube.com/watch?v=voz6S7ryWC0 Cook D, Bialoskurky Y, Fulton B, Fitch M, Gonzales J (2016) Game design patterns that facilitate strangers becoming “friends”. Project Horseshoe. Retrieved December 19, 2018, from https://www.projecthorseshoe.com/reports/featured/ph16r4.htm Dormans J, Adams E (2012) Game Mechanics: Advanced Game Design (Voices That Matter). San Francisco, California: Peachpit Dunbar R, Sosis R (2018) Optimising human community sizes. Evolution and Human Behavior, 39(1), 106-111. https://doi.org/10.1016/j.evolhumbehav.2017.11.001 Dunbar, R (1993). Coevolution of neocortical size, group size and language in humans. Behavioral and Brain Sciences, 16(4), 681-735. Retrieved December 28, 2018, from http://mnytud.arts.unideb.hu/tananyag/dunbar.htm Glaeser E, Laibson D, Sacerdote B. (2002) An Economic Approach to Social Capital. The Economic Journal 2002, 112(483), F437-F458. Retrieved December 28, 2018, from https://scholar.harvard.edu/laibson/publications/economic-approach-social-capital Group Cohesiveness. In Wikipedia. Retrieved December 28, 2018, from https://en.wikipedia.org/wiki/Group_cohesiveness Hall J, Davis D (2016) Proposing the Communicate Bond Belong Theory: Evolutionary Intersections With Episodic Interpersonal Communication. Communication Theory, 27(1), 21-47. Retrieved December 28, 2018, from https://onlinelibrary.wiley.com/doi/full/10.1111/comt.12106 Interpersonal Ties. In Wikipedia. Retrieved December 28, 2018, from https://en.wikipedia.org/wiki/Interpersonal_ties Koster R (2003) Small Worlds. Retrieved December 28, 2018, from https://www.raphkoster.com/gaming/smallworlds.pdf Koster R (2018) The Trust Spectrum. Retrieved December 28, 2018, from https://www.raphkoster.com/2018/03/16/the-trust-spectrum/ Lee E, Depp C, Palmer B, Glorioso D (2018) High prevalence and adverse health effects of loneliness in community-dwelling adults across the lifespan: role of wisdom as a protective factor. Cambridge Core. https://doi.org/10.1017/S1041610218002120 Marvin R (2018) Fortnite by the Numbers: How Many Hours Are You Playing Each Week? PC Magazine. Retrieved December 20, 2018, from https://www.pcmag.com/news/364107/fortnite-by-the-numbers-how-many-hours-are-you-playing-each Moai (social support groups). In Wikipedia. Retrieved December 28, 2018, from https://en.wikipedia.org/wiki/Moai_(social_support_groups) Putnam R (2000) Bowling Alone: The Collapse and Revival of American Community. New York City, New York: Touchstone Books by Simon & Schuster Sandstrom G, Dunn E (2014) Social Interactions and Well-Being: The Surprising Power of Weak Ties. Personality and Social Psychology Bulletin, 40(7). Retrieved December 28, 2018, from https://pdfs.semanticscholar.org/822e/cdd2e3e02a3e56b507fb93262bab58089d44.pdf Social Cohesion Approach. In Wikipedia. Retrieved December 28, 2018, from https://en.wikipedia.org/wiki/Social_group#Social_cohesion_approach Tamarit I, Cuesta J, Dunbar R, Sánchez A (2018) Cognitive resource allocation determines the organization of personal networks. Proceedings of the National Academy of Sciences, 115(33), 8316-8321. https://doi.org/10.1073/pnas.1719233115 Depp C, Palmer B, Glorioso D, Daly R, Liu J, Tu X, Kim H, Tarr P, Yamada Y (2018) Serious loneliness spans the adult lifespan but there is a silver lining: Feeling alone linked to psychological and physical ills, but wisdom may be a protective factor [Press release]. Eureka Alert. Retrieved December 28, 2018, from https://www.eurekalert.org/pub_releases/2018-12/uoc--sls121218.php |
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