What exactly is happening when changes in behaviour happen on a large scale? This is what I was thinking while reading Malcolm Gladwells Tipping Point.
I found this book very easy to read and he backs up his theories about how ideas spread by using interesting examples from a range of different fields such as disease control, crime statistics and social behaviour experiments. While none of these are new (Stanley Milgrams small world experiments and the game, Six Degrees of Separation are staples of pop culture) and have been covered before in the field of information science (Grannovetters Strength of Weak Ties and social network theory) he does bring them together very well.
He argues that changes can often escalate because of three rules – the Law of the Few (80% of influence is created by 20% of people), Stickiness (what makes the message memorable) and the Power of Context (e.g. the zero tolerance approach to minor vandalism which impacted on major crime in New York). This has inspired marketers who are interested in growing earned media. However, there is still debate over whether the data actually backs up Gladwells theories. It is fluffy, but neither marketing or storytelling are what I would call exact sciences.
For example, Twitter is my main network and I can definitely pinpoint the connectors (those social butterflys that introduce people from different walks of life), the mavens (those who share information in a helpful way) and the salesmen (those who are good at persuading others) who populate it. Whether it is an idea, a product, a service or a viral video, these three influencers appear to be always at work somewhere in the mix. Even my own decision to read the book was influenced by the Law of the Few. The connector was Seth Godin who mentions the book quite a lot for digital marketing. The information was shared by Maria Grau Stenzel in a MOOC I am participating in about transmedia storytelling. I was finally persuaded to read it by watching a video of Gladwell on Ted Talks after his natural style sold it to me.
The question is can you identify those types and behaviours in your own network?