Cascading benefits in social networks (& selecting suitable tweeters)

Posted on: October 31, 2009


Why do we make the choices we do? Levi and Kurzban have proposed that the common tendency for people to cluster in social networks can be explained by their theory of cascading benefits (PDF). Their argument is that human beings have developed an inherent, unconscious logic which can explain why we link to the people we do in social networks. I’m on a mission to explore network theory right now on the basis I will most probably write my dissertation using it in some way. I hope posts that spew from me in the process will not seem too abstract to practitioners and I’ll try and keep them as practically applicable as I can.

Essentially ‘cascading benefits’ works like this:

  • If I behave in a way beneficial to someone else, this will in turn benefit their connections
  • I unconsciously know this, which means I am more inclined to make friends with people who are friends with my friends
  • These ‘tertiary benefits’ I receive by benefiting my connections come to me more consistently if I am part of a dense network
  • The two factors above lead to clustering in social networks

In more detail:

“The logic of network externalities can be applied to the choices associated with partner selection. In particular, if actors derive benefits when particular others benefit, then a benefit to an actor benefits those that are tied to the focal actor.

For instance, imagine a cluster where each actor has an interest in the others’ well-being. When ego benefits alter, this delivers a secondary benefit – as an externality – to all of alter’s exchange partners. Because alter’s partners – A, B, and C – all have a stake in alter’s well-being, benefiting alter also benefits A, B, and C indirectly.

This means, in turn, that to the extent that A, B, and C believe that ego is likely to benefit alter, they have a stake in the continued well-being of ego. Thus, the benefit is likely to return to ego through the shared ties, as a tertiary benefit. As social networks increase in the number of connections, the possibility for benefit cascades increases.”

But what do I do on twitter?

In lieu of scientific research to interrogate this hypothesis myself, I might reflexively consider it in relation to my own experience as I have attempted to build up a twitter following (and select suitable tweeters) around a social object (e.g. social media, female entrepreneurs, environment). Are my choices driven by this ‘logic of network externalities’ or by deliberate, unrelated qualititative assessments? This is my rough list of what I scan for when I determine whether to follow someone / follow someone back:

Good Bad
Relevant tweets Any mention of making money online / on twitter
Lots of followers Many more ‘following’ than ‘followers’
Have they retweeted a tweeter I recognise and respect recently No bio and / or picture
Have they retweeted at all recently Lots of tweeted links with no explanation as to why they are posting them
Relevant bio Sexually provocative picture (don’t usually bother to click into a profile with one of these)
Can spot people I know in their following box on the right Lots of irrelevant tweets

Whilst this is a long list and I can sometimes spend less than five seconds deciding whether to hit the ‘follow’ button, I have indeed included an element which fits the cascading benefits theory. That is, checking whether my prospective follow has a history of benefiting an existing connection of mine. I had not consciously considered  this but it makes sense to me and fits the ‘cascading benefits’ theory, that if my connection is benefiting from their retweet I will benefit by association.

twitter network picture by Nimages DR


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