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Archive September 2009

2degrees? Shaun Hendy Sep 30

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A new mobile phone network called “2degrees” was launched in New Zealand earlier this year. As explained in its advertising campaign (fronted by the excellent Rhys Darby from Flight of the Conchords), the name alludes to the (alleged) only two degrees of separation between New Zealanders, as opposed to the six degrees that separate the rest of the world. Are Kiwis really so well connected?

The idea that people are separated socially from one another by at most six degrees has been around for a hundred years or so. Psychologist Stanley Milgram put it to the test in the late 1960s, using a chain-letter approach to delivering mail. Rather than addressing the letter directly to the intended recipient, Milgram sent the letter to a randomly selected intermediate, giving them the final recipient’s name and city, but not full address. He then asked the intermediary to send the letter on to a friend who they thought might be able to get it closer to its final target. The goal was to discover the number of social links that were needed to connect two people selected at random within the United States.

Although most of Milgram’s letters never reached their destination, those that did took on average only six links to be delivered. Hence the “six degrees” that supposedly separate us all.

With the arrival of the internet, these sorts of experiments have become much easier to conduct. You can play a similar game yourself at the Oracle of Bacon, a site which searches imdb to find the number of co-starring relationships that separate any actor from Kevin Bacon. Rhys Darby has a Bacon number of two: he co-starred in “Yes Man” with Albert Miranda, who in turn co-starred with Bacon in “Frost/Nixon”. The average Bacon number in the database is just under three, and the average Darby number is roughly three and a half.

Both the Oracle of Bacon and Stanley Milgram’s experiment illustrate that individuals within large social networks are connected by relatively short paths. Not all networks are “small”. Think of your family tree:  to follow your tree to your cousin, you’ll need four links (I hope) i.e. you to your parent to your grandparents to your aunt (or uncle) to your cousin. That’s already more than the average Bacon number, and in a network that only contains your extended family. Of course, you probably have direct social links with your cousin – this illustrates that social networks are different in structure to family trees.

Networks in which two individuals selected at random can be connected by a relatively small number of links are called small world networks. There are several popular books that discuss the science and mathematics of small world networks – I can recommend Six Degrees by Australian physicist turned sociologist Duncan Watts.

Scientists have identified other small world networks, including the internet and the world wide web. As I discussed in an earlier post, my research group has looked at networks of inventors. Networks of inventors turn out to be almost, but not quite, small world networks. Let’s call them medium world networks for now. They also share some features in common with the hyperlink structure of the web. But most interesting is that some of their properties do depend on network size, i.e. the properties of your collaborative network depend on the number of people in the network. This has implications for a small country like New Zealand – I’ll discuss this further in a later post.

So … are New Zealanders separated socially by only two degrees? Actually, a quick scribble on the back of the envelope suggests to me that it’s about four and a half: “4.5degrees” is not quite as catchy for a phone company, although it does conjure up an image of somewhere slightly warmer (possibly planet Earth by 2050). Still, I usually tell my students not to worry too much about factors of two, so I guess I can live with the “2degrees” ads provided they carry on being funny. Perhaps someone would like to design a Kiwi Milgram test to measure this …  how many links separate you from Rhys Darby?

Networks of inventors Shaun Hendy Sep 28

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Several people in my research group have been studying an OECD patent database recently. We were particularly interested in whether we could find evidence for collaborative networks of inventors. Almost all researchers collaborate with other researchers to some extent, but it was not clear to us that these collaborations would show up in the patent literature. While each patent application must name the inventors that have directly contributed to the invention, indirect contributions from unnamed researchers would be invisible to the database.

So when we started it wasn’t clear that we would find collaborative networks of inventors at all. However, we have now found many large communities of inventors who are connected by patents. In fact it turns out that these networks are similar in some ways to the small-world networks that exist in social groupings or between web pages, with hubs that form around highly inventive people. I’ll talk in more detail about structure of these co-inventor networks in another post.

The largest network we have found is in California, stretching from San Francisco to San Diego and connecting approximately 24,000 inventors. As far as we can tell, there doesn’t seem to be anything else like it in the world – the next largest networks are less than 10,000 inventors in size, and are dominated by large firms like Philips or Sun Microsystems. However, the inventors in this large Californian network come from a diverse range of organisations, seemingly a mix of small health-care and pharmaceutical companies. There is definitely something in the water in California.

Helsinki The other network that has fascinated me is much smaller. It consists of about 1300 inventors in the Helsinki region in Finland, whose patents are owned by Nokia (appropriately Nokia’s current slogan is “Connecting People”). A representation of the network is shown on the right – the red dots (“nodes”) show individual inventors, with the lines (“edges”) between dots indicating that the two inventors share a patent. This network formed as Nokia transformed itself from a relatively small consumer electronics company to a globally dominant mobile phone manufacturer over the period 1993-2008 .

Finland output growth The largest network we can find in New Zealand consists of less than 40 people. So I find it remarkable that a co-inventor network of 1300 people exists in a country with a population similar to New Zealand. Finland’s patent and publication statistics from the early 1990s do not suggest that they were any stronger than New Zealand in information and communication technology. Yet by the end of the decade they were vigorously patenting and writing papers in ICT, and had increased their electronics exports tenfold to more than NZ$20 billion per annum (shown on the left). No matter how you look at it, this was a remarkable economic transformation.

Of course, Finland was lucky that Nokia emerged with the right product at the right time, but to exploit this luck to become the dominant player in the world cell-phone market, they apparently drew on this very large pool of inventors.

Where did they get that inventive talent from? I gave a talk on this in June at MoRST where someone suggested that there may have been an influx of Russian scientists and engineers after the collapse of the Soviet Union. However, the inventors names in the database are distinctly Finnish – it appears that the Finns trained Nokia’s inventors in their universities. While in the 1980’s, less than 50 engineering PhDs were graduating from Finland’s university each year (close to New Zealand’s current total), early in the 1990s this started to grow, and by the end of the decade the figure had tripled. In a later post, I’ll look at this in more detail.

A measure of science Shaun Hendy Sep 26

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As a theoretical physicist and applied mathematician, I’m interested in using numbers to describe all sorts of phenomena. And as a researcher in the MacDiarmid Institute, I’m also interested in innovation. So for me, it’s natural to try to study innovation quantitatively. One of the goals of this blog will be to look at science innovation using tools developed to study complex systems, drawing on quantitative data sources and statistics.

What is already out there? In a New Zealand context, MoRST publishes an RS&T scorecard and also commissions a national bibliometric report from time to time – there is one due out this year. The Ministry of Education also recently published a bibliometric analysis of the Universities in order to assess the impact of the performance based research fund. Similarly, the Marsden fund commissioned a bibliometric study to look at the impact of scientific papers that were produced as a result of its funding.

A bibliometric study counts or analyses the scientific journal articles that scientists are publishing. It can give information on the subject areas scientists are working in, and can provide an assessment of the impact that those scientists are having in their field. One way to assess impact is through citations – i.e. looking at where and how often a particular journal article is being referenced by later journal articles. The value of bibliometric studies is controversial, particularly when they are used to rank individual scientists who are competing for funding. Nonetheless, as journals are the most important forum for communication of scientific ideas and results, bibliometrics is here to stay.

Another measure that is frequently used is the number of patents produced by a country. Patents are principally produced by researchers in the private sector, so they complement scientific publications, which are mainly authored by researchers in the public sector. MoRST’s RS&T scorecard has some interesting information on the patents produced by New Zealand. Further information can be obtained from national patent offices:  New Zealand’s Intellectual Property Office has a searchable database of patents. Counting patents has its drawbacks too. Assessing the value of a patent is a difficult task.

The OECD is another organisation that monitors scientific performance. Its studies are interesting because they put New Zealand’s scientific output into an international context. The OECD reviewed the New Zealand innovation system in 2007 – in this document you will find a large amount of financial data:  business expenditure in research and development, dollars spent on basic versus targeted research, etc. In fact, much of the quantitative discussion on innovation focuses on the dollars spent.

Another piece of the puzzle is provided by Statistics New Zealand. It publishes a report every two years on the number of scientists and researchers in New Zealand. The Ministry of Education also tracks the number and subject areas of advanced degrees (such as PhDs) granted at Universities in New Zealand.

What will I add to these sources? There is a wealth of data available, but it is held in diverse locations. One thing I’ll try to do is pull some of this information together. For example, I’ll look at how the number of scientific papers and dollars per researcher has changed over the past 20 years. I’ll also try to use new tools for looking at the data, particularly some of the methods that have been developed recently for studying complex systems. New Zealand’s innovation system is, if nothing else, complex.