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Influence et contagion
L'influence et la contagion dans la cyberculture
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The Structure of Online Diffusion Networks I #adoptions #patterns

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In order to identify generic features of online diffusion structure, we study seven diverse examples comprising millions of individual adopters. As opposed to biological contagion, our domain of interest comprises the diffusion of adoptions, where “adop- tion” implies a deliberate action on the part of the adopting individual. In particular, we do not consider mere exposure to an idea or product to constitute adoption. Conta- gious processes such as email viruses, which benefit from accidental or unintentional transmission are therefore excluded from consideration.

Although restricted in this manner, the range of applications that we consider is broad. The seven studies described below draw on different sources of data, were recorded using different technical mechanisms over different timescales, and varied widely in terms of the costliness of an adoption. This variety is important to our con- clusions, as while each individual study no doubt suffers from systematic biases arising from the particular choice of data and methods, collectively they are unlikely to all ex- hibit the same systematic biases. To the extent that we observe consistent patterns across all examples, we expect that our findings should be broadly applicable to other examples of online—and possibly offline—diffusion as well.

The remainder of this paper proceeds as follows. After reviewing the diffusion liter- ature in Section 2, in Section 3 we describe in detail the seven domains we investigate. We present our main results in Section 4, showing that not only are most cascades small and shallow, but also that most adoptions lie in such cascades. In particular, it is rare for adoptions to result from chains of referrals. Finally, in Section 5 we discuss the implications of these results for diffusion models, as well as the apparent discord between our results and the prevalence of popular products, such as Facebook and Gmail, whose success is often attributed to viral propagation. 

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There Are No Super #Influencers: The Reality about Influencers from the world of #NetworkScience

There Are No Super #Influencers: The Reality about Influencers from the world of #NetworkScience | Influence et contagion |
The influence of influencers is overhyped. We all want to believe that there are these super-hero influencers that can make dramatic changes to organizations, countries, and societies. The idea has...
luiy's insight:

The idea has been spread in pop-culture in books like Malcolm Gladwell’s the Tipping Point. Recent developments in Network Sciencehave shown that our understanding of influencers – the super-connected individuals in our organizations and society – is more or less wrong.


So what is the truth behind influencers? The science is still figuring it out, but here is what we have learned so far.


It’s all about Micro-Influencers

The super-connected influencer do not exist, instead there are micro-influencers – those that have slightly more influence than the rest of the population influencing those around them to spread their ideas and messages about certain topics. (I would consider my friend Andrew a micro-influencer, he got our whole group of friends drinking high-quality craft beer after he himself jumped into the cult of American craft beer drinking).


We use to think that the human social network was constructed like our airport network (also called scale-free networks), there are hubs in which most traffic can get to most places, thus have huge influence on the flow of information.


The truth is that there are no Chicago O’Hare, or London Heathrow individuals.  Why? Because the human network does not work like the airport transportation network. The human capacity to manage relationships is finite. Unlike our major airports, we cannot just construct another terminal in ourselves to deal with more traffic. We have a limited number of relationships we can actively manage and the reach of our direct influence is limited by the relationships we manage.


The average number of friends people have on Facebook is around 200 – but there are some Facebook users who have 2000 friends (the max for an individual account), which is only 1 magnitude greater, not 10 or 20 times greater like we would expect if our human networks were more like airports: like the difference between Colorado Springs Airport traffic and Chicago O’Hare.


Claude Emond's curator insight, January 16, 2014 6:54 PM

very interesting by Luis about the «myth» of super influencers in the cyberspace. How collective intelligence really works !