Game theory & social media marketing (4): Conclusions

The Royal Game of UR, Early Dynastic III, 2600BC, British Museum

[Part 4 of 4: Game theory & social media: Part 1Part 2, Part 3]

No, I’m no super lady, I don’t have no game whatsoever,
I put my high heels on and see how that goes, yeah
– Pauline, Sucker for love

Ask a mathematician why they like maths, and they will tell you that mathematics gives a definite yes or no. There is beauty in clarity. And, everyone likes to feel that they understand and have control over what is happening in their world. This feeling of certainty is reflected in the bottom two rows of Maslow’s hierarchy of needs: physiological and safety needs.

Tapping into fear and belonging

That said, we also love variety and surprise, which is the most popular information shared on social media. We crave new stimulus which is why we love games. We love the idea of chance or fortune transforming our lives for the better, and surely if we learn the rules, then we will succeed. And, that is why marketing has such a pull on us. Marketers tell us that we will have improved lives if we do/buy/or have what they are selling, and, marketers themselves will have improved lives too if we do/buy/or have what they are selling.

There are so many ways to market something, this link has 52 types of marketing strategies. The most effective, of course, aims at the bottom of Maslow’s hierarchy of needs – safety – which is why fear quite often drives news and coupled with specific instructions gives a compliant society.

Tapping into belonging is another way to market, which is why the connection economy and building friendship with your customers is gaining so much traction as a marketing strategy.

Modelling emotion and what-ifs

Modelling human emotion is impossible to do with game theory especially on social media, a fluid, still unknown, type of communication. We will never quite know who our audience is. We may target our demographic, but if they retweet or share something outside of that, then you never exactly know who is looking at your content, or how they will react to it. All game theory can do is offer interesting and potentially useful partial explanations to model a selection of what-ifs scenarios when employing different strategies.

In the last post (part 3), we looked at various game theory strategies from the aggressive to the altruistic, and saw that people generally behave like the people around them (hawk-dove) and that Kermit was in a bit of hurry to get together with his girl, which caused him to behave passive-aggressively, and probably not get what he wanted.

 Don’t be like Kermit

Game theory is a tool for social media marketing and the best application of it is recording trial and error attempts (with statistical significance) whilst using our emotional intelligence.

Be aware of your emotions and triggers (your personal competence) so you don’t get involved in a big wrangle either privately, which could damage a relationship, or publicly, which might be retweeted everywhere and could wreck your brand or reputation.  Even in the mathematics of game theory we need to understand other players moods and motives (social competence) and not assume anything. We need to ask for more clarification, so that when we do make a move, we do so with clarity and certainty that we are doing the right thing, and as any mathematician would tell you if you asked them, there is beauty in clarity for it gives us certainty and a sense of control, things which are harder to come by in our ever changing world.

Designing design: Solution spaces


[Part 11 of 12: 1) The science of the artificial 2) function, behaviour structure 3) form follows function, 4) no function in structure, 5) the medium is the message 6) types and schemas 7) aesthetics: attractive things work better 8) managing (great) expectations 9) colour 10) styles and standards 11) design solution spaces 12) conclusions]

The artificial intelligence community views a design space as something to explore as it if is a mountain or a wilderness. A space may be incomplete or the domain knowledge uncertain and this is reflected in the names of search techniques: hill climbing, branch-and-bound, hunter gatherer.

Fabulously nowadays we have massive computing power which can help us search through big data sets or solution spaces. However, in the broadest terms when we are looking at a solution space we are hoping to manage it by the following:


With constraints, we introduce boundaries which may potentially the number of solutions. It is this tension which can cause wonderful solutions such as when artists obey the haiku rules of 17 syllables: three lines of five, seven, and five syllables, to give us pared back poetry.

We can also introduce constraints by fixation on one thing such as cost, or efficiency and then we can see what solutions are possible.

Otherwise, we can use a more exploitative exploitation approach of what-if. What if we place an excessive load on this bridge? What happens then? Does the solution still work? What will we need to change to get it work?

Transformation, combination and exploration

Inside the solution space we synthesise and analyse by using some of the ideas this series has explored. We map our types and schemas or our models of aesthetics and affordances and link our function to our behaviour and then structure. But, when all else fails we can remove the constraints or even remove the boundaries or the domain knowledge which can lead us to moving outside the context.

Thinking outside the box

Sometimes designers do this on purpose, other times like the post-it note, new ideas are serendipitously discovered. SMS texting was originally invented for engineers to communicate with each other whilst working on mobile technology. Who could have anticipated that a tool which made engineers’ lives easier would appeal to mobile phone users as a cheap and cheerful way of communicating instead? The same happened to post-it notes, once the context of inventing glue was removed, the user was free to think of it as a really cool book mark.

With a solution space we can define what we are looking at, and what we are looking for, and then should we decide we want to look at it differently, or look elsewhere then we have a map and a plan, which is what all humans like to have in this information overloading world of ours.

Designing design: Great expectations


[Part 8 of 12: 1) The science of the artificial 2) function, behaviour structure 3) form follows function, 4) no function in structure, 5) the medium is the message 6) types and schemas 7) aesthetics: attractive things work better 8) managing (great) expectations 9) colour 10) styles and standards 11) design solution spaces 12) conclusions]

Managing expectations is the key to success in most areas of life, not just design.

When a design artefact is judged to be useless, it is often because it does not behave in the way the user is expecting. This is because there is a gap between what the designer intended and what the user is expecting, which in user interface design, Donald Norman calls the gulf of execution. Straddling this gulf, is the way to manage user expectations.


We all have models of how the world works (mental models), and of ourselves (self schemas) to explain and make sense of everything. In design, we have three models:

  • The designer’s model of how the artefact works.
  • The user’s model of how the artefact should work and how it actually works which changes with experience.
  • The artefact’s image of how it works  which is the way it looks which should be supported by the documentation or user manual.

These models should line up in order to match user expectations, but to do so, the designer has to provide the correct cues.



First proposed by psychologist James Gibson, affordance describes how the physical properties of an artefact will influence its function. So, round wheels are much more suitable than square wheels on your bicycle. It is easy to see that the round wheels go round, square wheels might make you think the bicycle is an uncomfortable seat.


When similar looking parts of an artefact or system work in a similar way then users can easily transfer what they have learnt from one part to another and have similar experiences. Consistency can be aesthetic, for example, the windows on a graphical user interface windows have the same layout, or the logo is the same on each restaurant chain outlet so the customer know what to expect. Consistency can also be functional such as how traffic lights work in a certain expected order: red, amber, flashing amber, green.


Constraints are used to indicate what actions are possible. These can be physical such as when barriers are put up at sporting events to direct crowds and traffic. They may also be psychological in symbols such as a skull and cross bones for poison or danger, or conventional which we learn, such as we stop when the  traffic lights are red. Or, they can be cultural such as what people wear during mourning, in some countries it is black, in others it is white.


Feedback is necessary to guide user behaviour. A dialog box can ask: Is this what you want to do? Less usefully it might say: No, you can’t do that.  The box really needs to add: but you can do this or this.


We all need a link between what we do and what happens, so if you are driving your car and turn the steering wheel left you expect it to turn left.


In previous posts, we saw that the asethetically pleasing lemon squeezer known as Juicy Salif had sacrificed some of it functionality in order to look good, as did the Lockheed Lounger. In the same way, the more function you add to an artefact, particularly in the cues which are needed to guide and manage user expectations, the less usable it becomes. Complex gadgets may look cool but if they are not functional their value is more asthetic than usable and will only satisfy a tiny section of determined users.

Designing design: Attractive things work better

Danson House

[Part 7 of 12: 1) The science of the artificial 2) function, behaviour structure 3) form follows function, 4) no function in structure, 5) the medium is the message 6) types and schemas 7) aesthetics: attractive things work better 8) managing (great) expectations 9) colour 10) styles and standards 11) design solution spaces 12) conclusions]

Attractive things don’t necessarily work better but we humans perceive them as doing so because we are more forgiving if an artefact or a person is good looking because they light up the brain’s reward centre and make us feel better when we are around them. We are attracted to attractive things.

A thing of beauty is a joy forever

There are many patterns which we find inherently pleasing:

The golden ratio is a pattern which appears in nature and art. It has two segments with the ratio of  0.618 between them. It has been used in designs such as the Stradivarius, the iPod, and da Vinci’s Vitruvian Man.

The rule of thirds is the golden ratio’s rough approximation. Using grids to design a layout, divide the design into a 3×3 grid layout and put the most interesting parts on the intersections and not in the middle row of squares. The asymmetry creates a design which is considered aesthetically pleasing.

Similarly, the Gutenberg diagram divides a display into four and assumes we read it from the top left hand corner to the bottom right from left to right. So, the main area to look at is the top left, the top right and bottom left are referred to as fallow areas – meaning there is less focus here, and the whole thing ends in the bottom right.

Unity in variety

Gestalt theory is the study of how humans recognise and interpret patterns and is the result of research carried out by German psychologists in the 1920s. Their works shows that we interpret things in space and give them meaning:

  • Proximity: items close together are in a group together.
  • Similarity: items which look similar are together.
  • Continuity: lines as continuous, even if they are not.
  • Closure: incomplete regular shapes as complete.
  • Figure and ground:  the figure in the foreground must be more important than the background.

We prefer symmetry, balance, consistency and alignment when we look at design solutions. The law of Prägnanz asserts that we will interpret images in the simplest way possible, ignoring noise and clutter. So, misaligned items may get ignored.

These ideas and more many more similar ones underpin graphic design and the design of 2D graphical-user interfaces, Designers challenge these ideas if they want to create tension which may lead to something cool or something disastrous.

Designing design: Function, behaviour, structure

astrolabe pic

[Part 2 of 12: 1) The science of the artificial 2) function, behaviour structure 3) form follows function, 4) no function in structure, 5) the medium is the message 6) types and schemas 7) aesthetics: attractive things work better 8) managing (great) expectations 9) colour 10) styles and standards 11) design solution spaces 12) conclusions]

The design process exists because the world does not always accommodate us humans, so we employ designers to create things or artefacts, to get the world to adapt to us. In this way, we can see that design is the science of the artificial.

One way of thinking about design is to categorise information into three groups: function-structure-behaviour, as follows:

The first step is for designers decide on the sorts of functions they want the new artefacts to be able to do and then they write descriptions that could potentially do that.  However, until the artefact exists in its physical form, i.e., it has a structure, it is impossible to predict if the artefact will function in the way the designer anticipates, especially when choosing materials – plastic behaves very differently to wood and so on.  Or, in the case of designing a website, a blog behaves very differently to an online store.

So, instead of going straight to the second step of trying to describe the structure of an artefact directly from a set of required functions, the designer will first try to describe the expected behaviour of an artefact, and probably do some sort of simulation (by building a prototype, or performing computational analysis) in order to see how the thing behaves and if it is different to the expected behaviour, and this even works with software.

So, I am currently redesigning my website as it’s looking a bit old, so if I think of it in terms of function, behaviour, and structure, what might happen?

  1. Function: What is the purpose of your website? (Currently, it is just my blog, but I would like it to showcase what I do.)
  2. Behaviour: What will your website do? (Describe what I do, potentially offer what I do?)
  3. Structure: What structure will your website take? (I should have an about-me page, a courses page, a books page,  links to what I do, or a membership area so people can access what I do directly.)

In this way we can see that once I divide how I want my site to behave and how I want it to be structured, it becomes easier to open up to new ideas. Had I just thought that I have a blog, which looks like a blog, it would have been harder to arrive at the idea of creating a membership area. I might never have even thought about it.