broadstuff

Last week I attended another event i think was very useful seminal in pushing Social Media forward, the ChinwagPsych event, which reviewed the emerging lessons from the emerging fields of digital psychology and anthropology. It was really good as well because the amount signal was high, and the amount of noise from snake oil, bullshit and hype was low. Here are some notes of mine from the event.

Nathalie Nahan, who wrote Webs of Influence, on Website design in the Social era.

- Trussst is what stops people buying online, as customer service/delicvery etc is unclear. Consumer reviews are good at creating trust, also earned media. Using recognised logos eg paypal also helps
- Often need to give people some sort of value upfront as unknown/ untested vendor (Freemium, 30 day trial etc)
- 30% of online shoppers and rising worried about privacy (about bloody time too)
- When they scanned websites to get missing f2f trust cues, they found yellow was the worst colour for trust, followed by red
- Websites need a very defined call to action button (Now this is really Web 1.0 old hat, but since Nathalie's talk, I've become really aware of how many sites still do not do this)
- Using the scarcity principle - "only X left in stock" - to create a sense of urgency, really works
- UK is culturally difficult to US, need to soften the hard sell -
- Tweet to unlock benefits seems to work well
- Humans focus on contrast, and on concrete stuff - eg money management website example "I will teach you to be rich" is succinct and to the point.
- Framing in terms of loss raher than gain is better, as Humans are more loss averse
- 10% of a population = tipping point, when people start to follow without thinking (Interesting, I've seen memetic algoritms that calculate that when say when cheating gets to about 5% of the population it then starts to spread rapidly)

Leigh Caldwell, Inon - Psychology of Pricing

- This is an emerging new field - cognitive economics
- Talked about improving profit via the "rule of 3" - Typically with 2 choices get a 70/30 split, 70% cheapest.
- Insert an expensive 3rd choice - 3 choices split 60/35/5 - fastest way to improve profit
- Concept of "anchoring" - set expectations of higher price first, people will choose next cheaper option
- Human brain treats spending money siilarly to pain, so give people something or offer a later payment
- If you make price complicated, befuddles customer, reduces ability to discern (I tried to ask Leigh why mobile Co's, Energy Co's etc do this, despete stromg evidence it puts off customers but ran out of question time)
- You must Price differentiate for different customer segments to maximise profits, but be prepared to lose some sales
- People will value what you price

Simon White, Draft Cb - Why are people NOT using all this stuff?

- Old models (persuasion) only lead to accidental success as 95% of decisions are instinctive, not rational/ logical
- People don't like change/new ideas, so try to rationalise to their past knowledge, and it seems to work "well enough" as new approaches haven't really had major impact yet
- New approaches are still complicated to use, no rules of thumb, no benchmarks
- Rapid Change, new "New things" every 6 months - overwhelming amount of data coming out and overwashing last new new thing
- "Institute of Decision Making" set up, linking Research to actual Application of these ideas

The new thing I got from Simon's talk was this:

- People buy things to achieve goals, they do not have a "relationship" with brands as such. And their real goals are the implicit goals, eg buy Mercedes to feel powerful
- 3 main implicit driver axes

(i) security
(ii) excitement (drives dopamine)
(iii) autonomy (drives testosterone)

- Intersections between the above 3 exist - then adventure, discipline, enjoyment (see my diagram at to of page)
- So move proposition to answer explicit and implicit goal. E.g. Oreo - explicit goal, treat child. Implicit goal - passing on your experience, childhood

Simon Hill, Wazoku - Open Innovation - A rereshingly free-from-hype talk about the reality of Open Innovation.

- technology is not the issue in Innovation
- people need to see the benefits,
- also must sort wheat from chaff
- need to put culture in place to force innovation
- Idea management is about process of generating, selecting and executing ideas, not about the 1 big idea
- Only about 5% of ideas will get executed

I then had to go to a client meeting, so missed a few talks and lunch (boo), returning in time to catch:

Steven Haggard & David Stillwell, Cambridge Predictive
I first heard about them awhile ago when they started to put together patterns of connected likes, on Facebook, they mentioned some typical insights e.g. people who like Terry Pratchett and computing tend to be introverted and Likes on Facebook can tell relationship status (I'll bet!!). They started to look at Business Applications, for CRM, trying to find predictive qualities of personality for honing the Marketing message; keywords, behaviour types etc. They mentioned as an example the Relentless fizzy "energy" drink going up against Red Bull etc:

- Its roots were in music roots so they started look at interconnections there
- looked at what energy drinkers like, by age, sex, etc etc on FB, and clustered the data into 200 like groups with interlinks,
- Saw that Relentless drinkers unique in Top Man U, Bad Diets, Classic heavy metal. So th
- Built Matrix of Energy drinks vs like groups, with probabilities on intersect.
- Overlay like groups with demography, and created a new new psychological profile layer above the "correlation" layer
- Relentless users are impulsive, neurotic etc, create narratives to fit
- Found that Music choice is a good proxy for personality index overall, so you can see eg Aerosmith and Journey hit different people
- Now working on Numerical score of musical affinity

Cat Jones, Unruly Media - Viral Video Chart

- built Unruly Sharerank algorithm by testing large no of hypotheses of what drives sharing vs actual sharing
- Myth #1 you can't predict sharing - you can, and quite accurately
- Myth #2 content must be funny - but you can do warmth or excitement as Main vector for eg
- 2 Video examples predicted - "3"s Pony doing a Fleetwood Mac Dance = funny and happy and warm; and Pepsi's Camaro = funny and nervous and excitement
- Camaro did as their aglorithms expected, Pony did much better - mainly due to an unpredicted factor, the horsemeat scandal at teh time
- Viral peak is usually day 2, on avearge 25% of all shares on 1st 3 days
- optimal time of video = c 3 min (We found the same for video clips when testing in 2007)

Milward Brown (Similar findings to Simon White, above)

- The only people who were shocked by behavioural economics were economists (rational man)
- $35bn Market prediction industry, only 2% modern tools - why?
- traditional tools are not that broken
- New methods are not that simple to use, and hard to transfer from specific project
- emotion is not everything, most people have very little resonance with most brands most of the time
- New methods give very different results but case law does not exist to calibarte them - very little published success.
- Also they are hard to understand

What was new is they have tested a number of these new approaches against Ads

- Most useful method they have found is facial response, map facial
happiness as Ad plays. Integrated with survey data from same people
- Shows key impacts across different cultures, and what people react to vs what they say they do
Can also check reactions at 2nd view etc.
- Online Behavioural Psych is more Nudge than Revolution

The next 2 talks were about Smart work, and were interesting in that they seem to apply a "psych" layer to the Quantified Self movement

Design by Day (Book on smart work) Nokia/Anthony Mayfield

- using mobile technology to improve productivity
- if you get 5 hours sleep a night you are no better than being drunk
- only a decade into ubiquitous connectivity, 3 years into smartphones, so started to look at what can be done
- use Design thinking to structure workflows, design Prototype Days to test what works/doesn't work, timeline a bad day, see what you can learn.
- Also looked at older ideas that neuroscience backs up
- Thinking is expensive, glucose is measurable - habit is lowest energy levels
- work day doesn't match how our brain works. We only have 3 - 4 hours a day at peak performance, yet we often waste it on doing emails and meetings
- Benjamin Franklin was a major designer of his day
- Need to close off little worries
- Know when to switch off, scheduling time for email and Twitter etc - McKinsey report showed multitasking is less efficient on all tasks

Prof Karen Pine - "Do something different"

- Use technology to remind you to do something different that is good for you, force behavioural flexibility
- people tend to use some behaviours too much, drives personality (locked in habits)
- brains like to save energy, repetition drives strong pathways. But this default is not always right way in every situation. Success can over- embed behaviours.
- If there is a gap between our behaviours and what is needed, it drives stress, eg: strong extrovert may not have introversion capability, creates stress
- Most effective way of changing people is not change what they know but change what they do, as otherwise they flip back to what they know how to do
- People develop by doing new things, trying to do same stuff in new ways

Benjamin Ellis, Social Optic

- how to use technology to change larger groups - uses social data to drive changes in organisations
- Amount of data in businesses has grown hugely, used to have data scarcity, now glut in flow and storage
- Unstructured data is the major challenge, we now store it and work out how to structure it later (I agree with Benjamin here, this is the major issue wiyh a lot of Corporate data)
- Old way of marketing - ask people, but they tend to give acceptable answers - different Co cultures drive different mindsets - measure attitudes, not behaviours
- New way - scrape social media behavioural data - tells are not only what people say, do - but how they do it eg how long they take - aim is to predict behaviours
- A lot of social network data is not behavioural, it's managed attitudinally
- In businesses using social media proxy data, main lesson is the shape of the graph
- Language used is an interesting tell, in the business social media, you can tell a lot of things from it, eg Sentiment
- Look at where people use common language, shows the social influence graph
- But can wind up with "beautiful mind" syndrome, seeing many many potential patterns
- Also need to factor out correlation, to only get causation - its very hard
- People also follow biases when given Big Data, anchor on the 1st thing they see, confirmation bias and bandwagon effect can take over
- Chris Anderson saying sheer volume would obviate theory - wrong. Nate Silver book better
- Game mechanics is using psychology to influence behaviours

Daniel Bennett & Marina Clement, Ogilvy Change: Case study - the missing £2

- Rory Sutherland started behavioural economic arm, heavy usage of outside academics. Case study was that people are stopping buying newspapers, so how do we sell them again. Approaches were
- 3 option choice architecture with dummy option (like Economist used)
- differentiate between tablet, PC and smartphone offerings
- Nudge 1 choice sleight of hand in use of deals (see Economist above)
- Nudge 2 choice overload
- Nudge 3 superiority bias - "ultimate" pack
- Nudge 4 - create easy to choose default

Those 4 "nudges" hit 257% ROI, I asked which ones had the most impact, they said they didn't know. I find that hard to believe

Fascinating and worrying in equal measures.....

We have been asked to be on the Microsoft Business Re-Imagined panel on the 15th of May, looking at the potential impact of Social Media in business. We've been consulting to and building social media systems for clients since 2005, and it seemed like this was a good time to boil down our experience down. Above is a simple value creation flowchart, and we look at how, in our experience, social media can impact value creation. Stripped to it's bare bones, a business creates sustainable value by increasing revenues and/or reducing costs. Social Media is a new set of technologies that can help in a number of ways.

Revenue Increase

Essentially, there are only 2 ways of increasing revenue, which is sell more stuff, or increase the price at current volumes. In my view, Social Media is more powerful (with current technology, anyway) in dealing with Consumer sales, rather than Business sales, as the main cost in a consumer sale is reaching the large mass of disparate consumers. With business sales the target market is much easier to identify, and there are less customers to contact so current approaches work well.

Sell More - Social Media is a potentially very powerful tool to generate new demand - to find new customers, to bring them to the enterprise, create trust, ease their purchasing journey, and help optimise website design to maximise sales throughput. Taking it to greater extremes, Social Media data can be used to start to psychologically profile your customer base to understand what sort of people may also be your customers. It is also a very powerful tool to optimise the product - to discover the features or configurations that customers really value, and you can identify what competitors do well and include those in your product. But it is not a substitute for existing methods today, it is an adjunct, it can't be the only tool. It is not an appropriate tool for overt "hard sell" marketing, for example.

Increase ARPU (Average Revenue Per Unit) - Social Media has two main functions here - to aid in communicating the value proposition of the product, and to improve the perceived value vs competitive offerings. Communicating the value is fairly straightforward, as it serves as an extension of traditional channels, with the added benefit is that it has a strong feedback loop so it is quickly possible to see what is working and what is not. It is also probably better at communicating implicit values than more traditional media. Social Media can also help to improve the pricing point by optimising product differentiation amomg dofferent customer groups, and find pricing points for these different customer groups. That feedback loop, and the data it drives, can be used to to find attractive product combinations, and to optimise the website design to maximise value per sale. Taking it to greater extremes, Social Media data can be used to start to psychologically profile your customer base to understand their hot buttons better

Cost Decrease

Again, essentially there are only 2 ways to reduce costs - reduce operating expenses (Opex) and reduce Churn (Customer defection). I will ignore Capital expenditure (Capex) for now. Social Media in my view is as useful in both consumer and business facing enterprises, as it's power is about increasing productivity and effectiveness in reducing costs

Reducing Opex - In most companies, there are two major cost areas - raw materials and labour, the sum of them is typically the "80/20" of the cost pie (companies with near zero raw material costs tend to be professional service businesess, with very high labour costs). So far in or experience the two major Social media impacts are from:

(i) getting better market information (both pre and after sales) from customer to company, allowing the company to both reduce costs or lead times of raw material while not reducing value, and being able to better place its human resources where it really matters - it can work like a real time value engineering approach. It's not just useful for line operations, social media can be used to influence better design and innovation, and can be used to increase "brain cycle cpacity" by tapping into customers and the overall milieu without having to employ it

(ii) getting a better flow of information between people in the company, so co-ordination is better (less balls are dropped because A didn't know what B knew about customer X) and spped of reaction is faster.

The third cost element, overheads, is interesting. I have some thoughts about using Social Media transaction data to better allocate some overheads, but I don't have a fully formed set of ideas and I haven't seen it put into practice anywhere yet.

Reducing Churn/Increasing Retention

Churn is often not well understood, as many businesses are not aware of the huge differences in cost between retaining an existing customer, and finding a new one. There is often an order of magnitude difference. Thus reducing churn can have a massive impact in cost reduction and revenue increase Social Media can be used to aid customer service, to serve as an early warning for customer problems, to find out what people really value in post sales service, and to improve the product lifecycle. Social media also means bad service is more likely to leave a company's reputation punished, which can also impact sales, as customers typically research online before buying. In saturated industries, having a better churn than the competition can radically alter the market share and strategic positions within a few business cycles.

A brief word on Capex costs - if Social media is helping a busines to make better use of existing assets, in theory it will slow down future Capex requirements - but Social Media technologies do have Opex and Capex costs of their own, and these are typically incurred early up, while the benefits are then gained over a series of cycles. Which brings us to the dreaded Return on Investment (RoI) question.

Return on Investment

For any new technology, ROI is hard to work out, as few case studies exist to allow calibration of cost and benefit. If history is any guide, new and risky ideas are typically implemented first where forces are greater than a pure ROI worry:

- Piloting: trying out the New new thing in some areas of the business, somethimes structurally, often though by "Intrapreneurs" who do it locally out of passion, or seeking promotion etc.
- Pressure: A company realises it will not succeed doing "Business as Usual", and has to do "Business as Different". Recessions are for this reason more likely times to see new ideas implemented
- Politics - needing to be seen to be "with it", intra-divisional rivalry etc - all these can drive early day projects

But eventually, for Social Media to take off and scale, believable ROI needs to exist. We are dubious of some of the various "Returns on" currently touted for Social Media, as it is hard to tell which are valid proxies for hard to measure benefits, and which are just Snake Oil. Our test is that if a proxy measure cannot be linked to an underpinning economic benefit logically, its more likely than not to be snake oil.

Other Impacts

So far we have seen 3 meta-impacts of Social Media occurring

Firstly, there is a synergy when multiple of the above areas are pursued. The marketing listening systems can influence the customer satisfaction and product design systems, the customer satisfaction system can improve the marketing message, better staff co-ordination can improve customer service and salesforce knowledge and thus effectiveness. In general as more information flows in a business, better decisions are made throughout the business. But its not a given - if organisation culture is not open, if individual reward structures do not encourage sharing, if management use the new dataflows to further expolit staff, these systems can go nowhere, even potentially accelerate problems as they are just better ways of making sure all the sh*t hits the fan.

Secondly, the same influencing ability that works on attracting potential customers can influence sentiment, and thus share price. But this has always been a temporary game in the past, and its unlikley Social media will be any better at selling the sizzle if there is ultimately no beef.

Thirdly, expanding on this, a basket case will be exposed far more quickly - disaffercted customers, employees, investors etc will make their feelings known. In teh old days, they sued to say one disgruntled customer would on average tell 7 people. Now they will tell tens, hundreds, thousands, will write on review sites, will push negative pages higher in the search rankings than "official" company narraticves, etc etc.

Beware the Snake Oil

There are too many Social Media snake oil merchants promising miraculous cures today. We talk about what Social Media can do above. This is what it cannot do:

(i) Replace the modus operandi of most businesses. Social Media is essentially a communications medium, like telephony or IT. Telephony made a major difference to the cost of selling retail insurance for example, but it did not replace insurance. Web sales has restructured the book industry, for example - but not replaced it.

(ii) Replace existing operating techniques - marketing and sales techniques, service techniques, working practices etc - or not straight away, anyway. This is for 2 reasons. Firstly, existing techniques exist because they still work a lot of the time, and Social Media is not an appropriate complete replacement, but is an adjunct to improve them in most cases. Now it may come to pass that eventually Social Media might replace, say, telephone call centres - it's plausiblee - but than a bunch of other things need to change too so it will more likely be a phased change, not a big bang. Secondly, history tells us that any new enabling technique actually doesn't replace the old, it usually just slowly supercedes it in the pecking order. The revolution will (in the main) be evolutionary.

(iii) Massively replace employees with other peoples' brain cycles - "crowd -X'ing" is overblown, because most businesses do not win the day on one-off surge efforts, but on day to day execution over many cycles, and to do that you need well trained and motivated teams, not an ever-shifting cast of part-time volunteers. Adhocracy is a great way of getting Ad hoc one-offs done, and we are all for it in its place - but its not a great way of delivering reliable, predictable products and services day in day out.

(iv) Be the Silver Bullet that saves the day. It will need to integrate into a number of other existing systems in any enterprise. Social Media is a new layer of enabling communication technology, that makes existing practices and processes more productive, or effective, or both. The degree of just what, where and how it is apporopriate will vary by company and industry.

(v) Ensure that This Time Things Will Be Different, save the Planet, bring Universal peace and Love, etc etc. Humans are humans, with the same foibles as they have ever had. Social media is not going to bring about a Business Utopia, where people give warm personal service all the time, all goods are maximum quality at minimum price, and cheaters never prosper - but because it lowers transaction costs, all those things will become a bit easier to police - and thus new ways of cheating, skiving and flogging lemons will emerge.

If we had to give our sanguine view, Social Media is the sort of cluster of technologies that today can give low % increases to all those areas we cover above - but once you sum up say a 5% increase in sales volume, a 5% increase in ARPU, a 5% reduction in OPEX and 5% reduction in churn, you wind up with a shift from (ay) 5% margin to near 30% margin. That is life changing for any business, but it has to be done within the current business systems to get the full impact. The medium may be the message, but it isn't the modus operandi*.

The Downside Risks

As with any powerful new technology, used improperly it can blow up in ones face. There are two main dangers that have emerged so far

- Leaky Ships: Sensitive information will leak more easily, so there does need to be more attention paid to keeping things tight where required. This is of course in direct opposition to the need to be open, and finessing the systems that handle commercially important data is still an emerging area and in our view is still a limit to Social Media reaching its theoretical potential.

- The Viral Faux Pas: The inappropriate and inopportune tweet that goes viral and pours opprobrium on the company is a frequent enough occurrence to be a Social Media standard trope. Apart from blaming it on the Intern, companies do need to be careful and have checks on their output, and damage limitation measures in place

The devil in doing all of this is of course in the details. So, we hope to see you on the 15th.....

(*With the exception of wholly new businesses that are Social Media businesses, of course - but that is the subject of another post)

After all this hullabaloo today, all you need to do is look at Apple over 35 years and you will see that they:

1. Are typically a very early entrant, integrating a variety of existing systems in a hitherto poorly served early adopter sector with promise, to create an easy-to-use product.

2. Use great design to create a demand for a high margin product. In recent years they have also become "cuter" at doing software as well as hardware after being caught out by the MS-DOS ecosystem

3. As that market matures, retreat to the highest profit quartile. Follow the money, not the volume.

Its a waveform. Find a wave, ride a wave, find the next wave. Quarterly numbers are irrelevant. They rode the PC wave very well, then the portable music device, then the smartphone, now the tablet.

What will they go after next? And will they be able to reproduce Job's genius for getting onto the board at the right time?

Update - my colleague Keith McMahon nailed the current tactic perfectly when he notes that market expectations currently outstrip reality, hence best strategy - buyback shares

There was a very interesting article in the Grauniad the other day, arguing that News can be toxic (the irony of the article being in a newspaper is there...). Its based on an essay by German writer Rolf Dobelli and argues that News deliberately plays to some of our more primitive instincts, so a glut can be bad for our health. In summary, the argument is:

News misleads. . It often looks at the wrong problem, or over-eggs the spectacular. We are not rational enough to be exposed to the press. Watching an airplane crash on television is going to change your attitude toward that risk, regardless of its real probability. If you think you can compensate with the strength of your own inner contemplation, you are wrong. Bankers and economists – who have powerful incentives to compensate for news-borne hazards – have shown that they cannot. The only solution: cut yourself off from news consumption entirely.

News is irrelevant. Out of the approximately 10,000 news stories you have read in the last 12 months, name one that – because you consumed it – allowed you to make a better decision about a serious matter affecting your life, your career or your business. The point is: the consumption of news is irrelevant to you. But people find it very difficult to recognise what's relevant. It's much easier to recognise what's new.

News has no explanatory power. News items are bubbles popping on the surface of a deeper world. Will accumulating facts help you understand the world? Sadly, no. The relationship is inverted. The important stories are non-stories: slow, powerful movements that develop below journalists' radar but have a transforming effect.

News is toxic to your body. It constantly triggers the limbic system. Panicky stories spur the release of cascades of glucocorticoid (cortisol). This deregulates your immune system and inhibits the release of growth hormones. In other words, your body finds itself in a state of chronic stress. High glucocorticoid levels cause impaired digestion, lack of growth (cell, hair, bone), nervousness and susceptibility to infections. The other potential side-effects include fear, aggression, tunnel-vision and desensitisation.

News increases cognitive errors. News feeds the mother of all cognitive errors: confirmation bias. In the words of Warren Buffett: "What the human being is best at doing is interpreting all new information so that their prior conclusions remain intact." News exacerbates this flaw.

News inhibits thinking. Thinking requires concentration. Concentration requires uninterrupted time. News pieces are specifically engineered to interrupt you. They are like viruses that steal attention for their own purposes. News makes us shallow thinkers. But it's worse than that. News severely affects memory. There are two types of memory. Long-range memory's capacity is nearly infinite, but working memory is limited to a certain amount of slippery data.

News works like a drug. As stories develop, we want to know how they continue. With hundreds of arbitrary storylines in our heads, this craving is increasingly compelling and hard to ignore. Scientists used to think that the dense connections formed among the 100 billion neurons inside our skulls were largely fixed by the time we reached adulthood. Today we know that this is not the case. Nerve cells routinely break old connections and form new ones. The more news we consume, the more we exercise the neural circuits devoted to skimming and multitasking while ignoring those used for reading deeply and thinking with profound focus.

News wastes time. If you read the newspaper for 15 minutes each morning, then check the news for 15 minutes during lunch and 15 minutes before you go to bed, then add five minutes here and there when you're at work, then count distraction and refocusing time, you will lose at least half a day every week. Information is no longer a scarce commodity. But attention is. You are not that irresponsible with your money, reputation or health. Why give away your mind?

News makes us passive. News stories are overwhelmingly about things you cannot influence. The daily repetition of news about things we can't act upon makes us passive. It grinds us down until we adopt a worldview that is pessimistic, desensitised, sarcastic and fatalistic. The scientific term is "learned helplessness". It's a bit of a stretch, but I would not be surprised if news consumption, at least partially contributes to the widespread disease of depression.

News kills creativity. Finally, things we already know limit our creativity. This is one reason that mathematicians, novelists, composers and entrepreneurs often produce their most creative works at a young age. Their brains enjoy a wide, uninhabited space that emboldens them to come up with and pursue novel ideas. News closes, not opens, minds.

Society needs journalism – but in a different way. Investigative journalism is always relevant. We need reporting that polices our institutions and uncovers truth. But important findings don't have to arrive in the form of news. Long journal articles and in-depth books are good, too.

The author says he "has now gone without news for four years, so I can see, feel and report the effects of this freedom first-hand: less disruption, less anxiety, deeper thinking, more time, more insights. It's not easy, but it's worth it.". I must say I did the same, a similar time ago, after spending an extended period outside the UK and realising missing out on the daily News had a similar effect. I prefer to read "the News" once a week from journals eg the Economist, as very little that happens on a day to day basis is much more than mental chewing gum.

So here's the kicker for this article. What I have been using, a lot, over the last few years is social media of many forms. I am increasingly coming to the conclusion that the more immediate types (like Twitter etc) have a similar effect to News if over-consumed and have started to curtail my usage of it too (except for blogs, which I see as the more investigative element). If you replace the word "News" with "Social Media" in the above passage, it is largely still true in my view.

Thoughts?

Source: FRS blog, Princeton


Picked up from the New Scientist:

Sociologists have long known that people have fewer friends than their friends do, on average. This strange conclusion, known as the friendship paradox, arises because of sampling bias: people with a larger number of friends are more likely to be your friend, so they get counted more often.

Now Nathan Hodas and colleagues at the Information Sciences Institute in Marina del Rey, California, have shown this holds true on Twitter, too. The team analysed 5.8 million Twitter users' followers and followees (which they dubbed friends) and found that nearly all users were less popular than both their friends and followers - perhaps not surprising, since celebrities like @justinbieber and @ladygaga massively tip the scales.

What's more, the researchers also found 88 per cent of users tweet less often than their friends, rising to 99 per cent when completely inactive users are removed, and 79 per cent of users post fewer virally spreading links than their friends.

Re the Friendhsip Paradox, it is also seen on Facebook - NYT

You spend your time tweeting, friending, liking, poking, and in the few minutes left, cultivating friends in the flesh. Yet sadly, despite all your efforts, you probably have fewer friends than most of your friends have. But don’t despair — the same is true for almost all of us. Our friends are typically more popular than we are.

Don’t believe it? Consider these results from a colossal recent study of Facebook by Johan Ugander, Brian Karrer, Lars Backstrom and Cameron Marlow. (Disclosure: Ugander is a student at Cornell, and I’m on his doctoral committee.) They examined all of Facebook’s active users, which at the time included 721 million people — about 10 percent of the world’s population — with 69 billion friendships among them. First, the researchers looked at how users stacked up against their circle of friends. They found that a user’s friend count was less than the average friend count of his or her friends, 93 percent of the time. Next, they measured averages across Facebook as a whole, and found that users had an average of 190 friends, while their friends averaged 635 friends of their own.

Studies of offline social networks show the same trend. It has nothing to do with personalities; it follows from basic arithmetic. For any network where some people have more friends than others, it’s a theorem that the average number of friends of friends is always greater than the average number of friends of individuals.

This phenomenon has been called the friendship paradox. Its explanation hinges on a numerical pattern — a particular kind of “weighted average” — that comes up in many other situations. Understanding that pattern will help you feel better about some of life’s little annoyances.

In fact its a power law thing, in any network the "connectors" at the centre of friendship nets have a large number of friends, the less connected on the ouskirts have far fewer, so the "average" is higher than the average peripheral user owing to the high score of the connected Ones - see picture above. (Read the maths in the article, its a very good primer on social graph link weightings). The other highly connected strategy is to be a Social Butterfly, a being peripherally connected to many friendship nets

In short, unless you are the social hub of your friendship network, or a social butterfly, you will suffer from the Friendship Paradox - its one of the Power Laws of Nature.

At the top of the South Sea Bubble of 1711-1720, investors were eagerly pouring money into an enterprise advertised as:

"a company for carrying out an undertaking of great advantage, but nobody to know what it is"

At the (current) top of the Bitcoin Bubble (2011 - ?) investors are pouring money into:

"a company* for carrying out an undertaking of great advantage, with a currency that doesn't exist, generated by a method that nobody is to know what it is (and wouldn't understand if they did)"

This time, of course, It Will Be Different.....

Or alternatively, read George Santayana


* I use the term loosely

Bitcoin crashed today, spectacularly (see 3rd diagram below). To protect your wealth there are 3 things you need to know, all fairly well documented from other bubbles:

1. It crashed before, the last time there was a major frenzy, and it took years to recover. In 2011 to be precise, we wrote about it then, here was the graph at the time:




2. Bitcoin is a speculator's toy, and the fact it rose so fast (from c $15 in January 2013 - approximately its crash price in 2011 - to more than $215 in April) is a burst waiting to happen, and ordinary people have been buying it in droves over the last few weeks (and twittering about it - that is the equivalent of cabbies giving you stock tips) means that We Are Here



In fact, if you want to see that in actual crash-o-colour this is it



3. the last thing you should know - its a Virtual Currency fercrissake, it doesn't exist! You don't even have to go to the trouble of printing real paper phoney money if you want more, you just flip a switch and make more. OK, I'm simplifying, but you get my drift - In this Digital Age I think we need to invent Broadstuff's Law - Don't speculate on assets which cost ~ $0 to produce more of.

(Update - I have been rightly pulled up in the comments, what I meant by "produce more of" is the marginal cost of generating another bitcoin/virtual currency of your choice, once you are set up to mint them)

I know, I know - you can't make more Bitcoins, we are told. The software is safe, its based on the principles of cryptography*. Wanna bet? If you go back to March 2013...(Wikipedia)

"The fork of March 2013

On 12 March 2013, a bitcoin server (also called a "miner") running the more recent "version 0.8.0" of the bitcoin protocol created a large record in bitcoin's transaction log (called the blockchain) that was incompatible with earlier versions of the bitcoin protocol due to its size. This created a split or "fork" in the transaction log. Users ran the more recent version of the protocol while accepting and building on the diverging log as other users ran older versions of the bitcoin protocol and rejected it. This split resulted in two separate transaction logs being formed without clear consensus, which allows for the same funds on both chains to be double-spent. In response, the Mt.Gox bitcoin exchange temporarily halted bitcoin deposits.[45] The price of a bitcoin fell 23% to $37 on the Mt.Gox bitcoin exchange as this event occurred but subsequently rose most of the way back to its prior level of approximately $48."

We have been here before, people.....

We warned ya with Second life in 2006, we warned ya with Bitcoin in 2011, and we will warn ya again, and again. You're better off investing in Tulips or South Sea property.

*As it happens, we have more than a passing knowledge of cryptography, and its worth knowing its seldom the algorithms that are corrupted, but the men-in-the middle in the chain often can be.

For those who may have missed it, Margaret Thatcher, British Prime Minister in the 70's/80's, died yesterday. She was, according to the commentariat consensus, "extremely divisive". "Extremely" doesn't factor in our more precise world of Big Data Analysis (we used to call it data analysis, but what with inflation - you know how it is these days), so we decided to see just how much, and set our trusty old media analysis engine onto Twitter for a spell of Big Data bump n' grind (the term Thatcher is still ticking over on Twitter faster than a petrol pump eats pound notes by the way).

Anyway, much Big Chugging later and we can say safely that Twitter is about 44% against and 39% for Margaret Thatcher, ie the ratio of For : Against is about 1.13:1. The error on sentiment analysis is typically 10 - 15% so its near as dammit a wash in terms of divisiveness between the Maggie haterz and fanz (The Twitter demographic is still more left leaning than the national average, so I'm not that surprised it swings slightly to the left, as it were). An Ipsos/Mori poll shows that she is still the most popular post war British Prime Minister by some way, but she was seen as the most capable (39%) far more than liked (22%). For comparison, runner up Tony Blair was also "liked" at about 26% but seen as only 27% capable. The rest make for pretty sorry reading.

What is more interesting though is what is meant by "extreme" - to have a total of 39%+44% = 87% taking a position is a very high %, usually reserved for spats about various 'isms and causes du jour on Twitter, and even then many people tend to play the more even handed (or popcorn eating sports fan on the bleachers) role. For comparison the average Social business would be delighted if more than about 20% of their twitterstreams got really passionate one way or the other (a national broadband outage would possibly do it), and the parallel-running Twitter'Meedja discussion* about MumsNet got to about half that at its peak.

As to actual topics of - ahem - "conversation" in the Thatcherstream, the graphic above by Martin Belam (@Martin Belam), though data-poor compared to our big data crunth-a-thon, and far more tongue in cheek, actually captures the zeitgeist of the online discussion* very well.

In vitriol veritas, as they say.....

*spitting competition