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Social and Family Gaming #3: Fun and being social

I’m not going to try to carve out a whole theory here, but rather I want to try, by critique to point at the open spots for social and family gaming. Really for all I know the psychology of fun is understudied. One can open recent textbooks on social, personality and developmental psychology and not find the words “fun” “enjoyment” in the index or as topic (if you know good texts that do, ones with actually are based on sensibly controlled experiments that is). Luckily serious psychology books are at the same time full of results about social behavior, benefits from having friends etc. We even have results that for many internet and computer game users, the social plays a very important factor.

It’s sort of common wisdom that games are about fun, maybe we call activities games because we do attribute to them fun in some way or another.

The reason why this is so interesting is because what is “fun” or perceived as being fun, defines game design. Certainly there are different views on this around and I already mentioned Dani Bunten Berry in part #2. Her famous quite epitomizes that the social trumps individual achievement and solitude in her mind.

Game designers like Raph Koster talk about fun, and he refers to a model that he credits to Nicole Lazzaro that categorizes fun into 4 groups. “Hard Fun”, “Soft Fun”, “Altered States” (Raph tends to call this “Visceral Fun”) and the “People Factor” (or Raph’s better term “Social Fun”). Really at least the credit for “Hard Fun” should go to Seymore Papert.

I find this categorization fine enough. Two of them deal with the social in some way:

*) “Altered States” according to Lazzaro can be “[..] the enjoyment from their internal experiences in reaction to the visceral, behavior, cognitive, and social properties”. Lazzaro really does not elaborate about those “social properties”.

*) And of course there is “the People Factor”. Here Lazzaro has more to say about the social:

“Many player comments center on the enjoyment from playing with others inside or outside the game. In addition to buying multiplayer games players structure game experiences to enhance player to player interaction. Participants play games they don’t like so they can spend time with their friends. Wisecracks and rivalries run hot as players compete. Teamwork and camaraderie flourish when they pursue shared goals. Dominant emotions include Amusement, Schadenfreude, and Naches. [..]”

That is fair enough. In practice I think there are two main challenges to these theories as they are set up and elaborates.

First one of those is the theory of emotions, another tricky topic in psychology but certainly more developed (that one you will find in virtually any textbook in some form). The sets of emotions most characteristic to a gaming experiences are described by Lazzaro as these:

*) Fear, surprise, disgust, Naches/ Kvell (pride for the accomplishments of others), Fiero (triumph of overcoming hard obstacles), Schadenfreude (gloating at the misfortune of others), wonder

What is curious about these is that only two are inherently about social emotions: Naches and Schadenfreude, and only one, namely Naches is positive. Even more curious is that most of them circle around achievement (certainly both Naches and Schadenfreude do).

A whole set of emotions or socially relevant feelings or states are missing from the list. Belonging, attachment, altruism, empathy, sympathy, support, affection. All are missing as potential states or parts of enjoyment.

Raph Koster cites Lazzaro’s model when discussing social fun he says: “One of the most fun parts of the game is [..] Schadenfreude, which is to say gloating is one of the most fun parts of games.” That’s the only discussion social fun gets. Raph continues: “Games honestly mostly focus on hard fun”.

So not only is the most important social emotion for Raph Koster (hopefully in jest) a negative one, but the most important type of fun is hard fun that doesn’t actually intrinsically talk about social but about individual challenge. But also Lazzaro sees this similarly when she is cited in the following way: “Video games, for example, fall into the category of what Lazzaro calls “hard fun” — fun that’s both frustrating and challenging. Creating video games isn’t about designing a smooth user experience, she says. Indeed, in a good game, players should fail in what they are trying to do 80 percent of the time.”

(I’m not sure if 80 percent of parents would agree that it’s a great idea that their child fails 80 percent of the time. Certainly Raph likes to emphasize the importance of teaching failure – possibly to a fault – by missing to carve out the important boundary between fun and frustration, and the important boundary of motivation by feeling competent enough to master the next challenge (“flow”) to the disillusion of being not capable to reliably achieve success. But this is an aside, that is didactic more than social.)

That is, at least some game designers overlook the social fun, and the visceral aspect of fun that is social. But I think there is more to this as well. Overcoming challenges is only one aspect of what we as people have to learn. We have to learn how to handle our emotions, how to interact with others, and how to meet our social needs.

This is an important aspect of family gaming that doesn’t fit the all to heavy if not pure challenge model of “hard fun” alone. We play social games not just to gloat and be proud of the achievement of our beloved ones. We also play social games to socially interact, learn about each other, foster social skills, form bonds, explore others in a safe context of an artificial game environment, learn to cooperate, learn to give in, learn to support, learn to empathize, learn to see things from someone else’s perspective, learn to argue with grace, learn to be able to accept that multiple points of view are present, learn to cope with interpersonal frustrations, learn to unwind together. And of course learning to not gloat and be a graceful winner as much as a proud and respectful loser.

A lot of social behaviors are about the ability to not win for the sake of someone else, to forgo competition for the sake of preserving a social bond, to seek activities that are cooperative rather than competitive.

The prevailing problem with family and social gaming may be that a lot of game theorists haven’t understood all aspects of fun and focus on one type only. And by focusing on this one type, exclude the types that matter to many social settings.

The theory of social fun in games seems starved. Social fun is not just gloating over another or having pride that another beat a challenge. It’s having a hearty laugh at an odd game situation, it’s supporting others on challenges they cannot master on their own, it’s making effort that is not rewarded by anything but the gratitude of another.

Some games are “fun” for these social components. People sharing their weird sims story with friends or even jointly playing sims despite the lack of immediate challenge. People hopping around MMORPGs without any points scored or ranks gained, emoting and chatting for long periods of time. Groups of people hanging on team-speak for hours cracking jokes or trying to solve a situation together. Some of the games are fun despite not having been aware of the social needs. People made it fun for themselves despite the game design. However many recent successful games are aware of the social and add social support to the game and cooperative activities. But there are pitfalls when the game itself becomes a barrier. Not so oddly, in SOEs study about RMT at Station Exchange one of the most important reasons to buy was for people trying to overcome separation with others they wanted to play together with.

Above all social fun disappears if you simply cannot do things together.

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Signal to Noise ratio, data and explanation models in WoW subscription analysis

There is a recent buzz around WoW subscription and activity evolution. The first to put this out where WoWInsider showing data and asking “Why are people leaving WoW?” It then spread through the blog space that I read like it does, popping up on Raph Koster’s, Joystiq, Tobold’s blog and more.

I think there are a few things to be said about this as it stands right now, just from a pure data and analysis perspective. But why? Well one of the more interesting reactions to the graph is Raph Koster’s graphical analysis. He claims that a Bumb curve with an exponentially declining asymptotic tail (sorry for the math lingua, this basically just means that you have a smooth increase to a maximum, then it curves back down, but leaves an ever-diminishing tail that never hits zero). Raph proceeds to explain the WoW census data using this curve, overlaying new bumps at what he claims to be expansions of the market or other bumping factors (like a chrismas rush).

I found this analysis intriguing, but above all… just plain speculative. Mostly because the method is flawed. Let me explain why. Or rather let me credit the kinds of sources that have tought me why. The most accessible is the lovely book called “How to lie with statistics” by Darrel Huff which came out in the mid 1950 (old crap so to speak). It also contains a passage on how to make graphs represent just about anything. I found a short summary of the basic idea that unfortunately uses straight lines and rescaling, but there are many more tricks.

Let me try to explain what the pitfall with Raph’s argument is. The short version is that sums bump function is a very nice candidate to describe almost any data. The tail doesn’t make a big difference here because it’s drowned in the noice floor. The flexibility of the bumb function is that you can approximate rapid peak data with a steep hump that will go away quickly, you can approximate slow increases and decreases with a wider bump.

A longer version would show how you can, having essentially two variables to play with per bump function (height, width) one can match the piecewise slope of almost any function, one would go along to show that in the limit of vanishing width you end up with standard sampling, which of course can represent anything up to sampling frequency and that by keeping the height bounded you can always keep the error in the tail bounded. But basically that’s just the mathy and rigorous way of getting to how broad a set of functions one can approximate with these bumps.

A flaw in Raph’s explanation is that he actually doesn’t have ways to explain why he chose particular heights and widths in approximating the function. Take the second to last bump in his graph. This one has a very shallow height, but is rather wide. Why would one see this? There isn’t a real explanation hence one could as well assume that the curve landed there to help approximate the finer structure of the slope to get to the next bump.

But don’t get me wrong. This doesn’t mean that a bump-with-tail model isn’t helpful, or even justifyable. It just means that, because it’s so universal, you really have to take it with a big grain of salt.

Raph for example claims that:

Assuming that the title is equally available everywhere, you can predict the peak from literally three data points, which you can get literally in the first few hours of launch.

But to the best of my knowledge that is really just a hypothesis. And there really are good questions to be raised about it. So can a title, not screw up later? I think it was Tobold who pointed out that Vanguard had a rather uncharacteristic progression (can’t find the link right now, so I may have to correct this), which mostly meant that stuff didn’t quite look like the bump model.

Finally we don’t get an underlaying model explanation for the bump itself. One could try to see it as a probability distribution of some stochastically modeled situation (i.e. it’s complex, so lets pick a randomizing assumption that is valid for our setup at least in an approximate way). It could be Poisson which has a skewed gaussian distribution like Raph’s bumps, but the model there talks about onset probabilities of events happening (people being enticed to buy and subscribe to the game) or a Weibull distribution (which models things failing over time with some probability. i.e. people losing interest in the game for some factor). Weibull is more attractive I think but we really don’t know. It could well be both. But a Weibull model would not justify Raph’s claim that the first couple of hours determine everything of the bump, because failure reasons actually depend on the game’s desirability as it operates. The advantage of these models would be that one could give tangible reasons for the bump shape. Why was it flat, why was it high etc. We are lacking that.

But anyways, bump model or not. The WoW decline is an interesting story and the blogsphere has brought up numerous arguments: bump shapes, people holding off till after the expansion, the nature of the expansion itself, releases of other games like LOTRo. But as with any data analysis we’ll really have to wait and see more evidence. Does the increase in LOTRo qualitatively match a decline in WoW. Have there been questionaires explaining the cancelation of subscriptions (Blizzard actually does have exit questionaires) etc etc. For now it’s a happy place because we can speculate on one graph. MMOGData for example doesn’t yet carry any information of a decline of subscriptions for WoW, so it really is just one source.

So there really is a lot of noise and not that much signal yet.

TBC Raiding Buzz

Hmm I missed NewBreed’s post about TBC raiding that really addresses some aspects that I more abstractly talked about when discussing Blizzard’s donut model and the sociel ties issue. But luckily Tobold picked it up. Have a read.

 P.S. June 1: Here’s a german blog entry discussion this too.

Welcome to the Noise Machine

Yes, so here I have it. I have finally decided to try this blog thing that folks have been raving about. In fact it’s probably old-fashioned by now, but hey. I was never one to seek the most popular, but rather what works.

I want to write about a few things, but not quite yet. Stuff like MMO design and what works for me and what doesn’t. About online culture and the way people flame each other to death for no apparent reason, about fun and not so fun. And whatever else I can squeeze out on a boring afternoon.

For now it’s welcome, to something that says nothing at all.

P.S. And yes, possibly any catchy phrase is trademarked. What a bummer.