Comments on: Network analysis and the challenge of emergence http://aidontheedge.info/2009/11/19/network-analysis-and-the-challenge-of-emergence/ Exploring complexity sciences in international development and humanitarian aid Thu, 02 Sep 2010 08:36:11 +0000 hourly 1 http://wordpress.com/ By: giulio quaggiotto http://aidontheedge.info/2009/11/19/network-analysis-and-the-challenge-of-emergence/#comment-35 giulio quaggiotto Tue, 01 Dec 2009 14:15:25 +0000 http://aidontheedge.info/?p=296#comment-35 on a related topic, you might be interested in the presentations from the recent Harvard workshop on social influence in political networks - they shed some light on the question of centrality (or lack thereof) http://www.iq.harvard.edu/blog/netgov. The Web Ecology project has also done some fascinating analysis of twittering during the Iranian election - and emerging patterns during that period. Cheers, Giulio on a related topic, you might be interested in the presentations from the recent Harvard workshop on social influence in political networks – they shed some light on the question of centrality (or lack thereof) http://www.iq.harvard.edu/blog/netgov. The Web Ecology project has also done some fascinating analysis of twittering during the Iranian election – and emerging patterns during that period.

Cheers,

Giulio

]]> By: rick davies http://aidontheedge.info/2009/11/19/network-analysis-and-the-challenge-of-emergence/#comment-25 rick davies Sat, 21 Nov 2009 11:43:05 +0000 http://aidontheedge.info/?p=296#comment-25 I was surprised to read that Duncan Watts thinks that underlying the development of centrality measures is “the assumption that networks that appear decentralised are really not at all…” Many different types of centrality measures have been developed over the years. UCINET network analysis software will analyse about a dozen different types of centrality in network data. Most of these are measures of the centrality of individual actors in a given network, not measures of the structure of the network as a whole. In any network, including randomly constructed networks, there will always be some actors who are more central than others. And those differences will have consequences. The internet is a classic emergent network structure. Yet, I think Google’s Page Rank algorithm, which is the basis of its searching facility, uses a variant of a centrality measure known as Eigenvector centrality. This “second hand measure of centrality” assumes that “having links to many other pages is less important than having links to many other pages which themselves have many links to other pages”. Re Watt’s other comment, “What if important innovations originate not in the core of a network but in its peripheries, where the chief information brokers are too busy to watch?” Many would argue that focusing on core versus periphery is a false choice. I recommend Ronald Burt’s “Brokerage and Closure: An introduction to social capital”. In his view, and that of many others in the same field, the ability to broker new connections between disparate networks is as important as the ability to capitalise on that brokerage by having access to densely interconnected parts within those networks. Innovation not only involves discovery but also use and adoption by others. The whole dichotomy of centre and periphery is a bit of an artifact of the way we see networks. By necessity we are always only viewing part of a much wider network structure. That applies when looking at human societies and when looking at wider biological systems, and probably further afield still! By the way, appreciation of the complexity of networks goes back a long way in history and philosophy. My favorite example is “Indra’s Net” Read the Wikipedia entry here: http://en.wikipedia.org/wiki/Indra%27s_net I was surprised to read that Duncan Watts thinks that underlying the development of centrality measures is “the assumption that networks that appear decentralised are really not at all…”

Many different types of centrality measures have been developed over the years. UCINET network analysis software will analyse about a dozen different types of centrality in network data. Most of these are measures of the centrality of individual actors in a given network, not measures of the structure of the network as a whole. In any network, including randomly constructed networks, there will always be some actors who are more central than others. And those differences will have consequences.

The internet is a classic emergent network structure. Yet, I think Google’s Page Rank algorithm, which is the basis of its searching facility, uses a variant of a centrality measure known as Eigenvector centrality. This “second hand measure of centrality” assumes that “having links to many other pages is less important than having links to many other pages which themselves have many links to other pages”.

Re Watt’s other comment, “What if important innovations originate not in the core of a network but in its peripheries, where the chief information brokers are too busy to watch?” Many would argue that focusing on core versus periphery is a false choice. I recommend Ronald Burt’s “Brokerage and Closure: An introduction to social capital”. In his view, and that of many others in the same field, the ability to broker new connections between disparate networks is as important as the ability to capitalise on that brokerage by having access to densely interconnected parts within those networks. Innovation not only involves discovery but also use and adoption by others.

The whole dichotomy of centre and periphery is a bit of an artifact of the way we see networks. By necessity we are always only viewing part of a much wider network structure. That applies when looking at human societies and when looking at wider biological systems, and probably further afield still! By the way, appreciation of the complexity of networks goes back a long way in history and philosophy. My favorite example is “Indra’s Net” Read the Wikipedia entry here: http://en.wikipedia.org/wiki/Indra%27s_net

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