I hate to be that guy, but I think your plot does more to disprove your hypothesis than it does to prove it.

There doesn’t really seem to be any trend there at all.

Engineer, thanks for the critical eye – you’re absolutely right, the data could be read either way to prove or disprove the hypothesis. However, there are some compelling examples that do fit the model. Specifically, I think the Americas compared to Europe is an interesting dynamic. Canada, Mexico, and the United States all have low density and low adoption. European countries, by comparison, all have a higher population density and higher mobile penetration as well.

Country………….Pop/km2……….Mobile Index
Netherlands…………………395……………..101
United Kingdom……………246……………..106
Germany……………………..232………………92
Italy…………………………….193………………117
Switzerland………………….176………………90
Czech Republic……………..132………………111
Denmark……………………..127………………98
Portugal………………………114………………109
France…………………………110……………….77
Spain…………………………….89………………..99
Mexico………………………….53………………..45
United States………………..31…………………72
Canada…………………………..3………………….52

Like I said, it’s by no means scientific, just an interesting conversation starter. For a proper comparison, I think you’d also have to look at the percentage of the population that lives in high-density areas versus low-density areas within each country. In the end, perhaps it just comes down to an urban versus rural argument.

Hey Naumi,

I suspect you would see a slightly better correlation if you can get data on average house sizes. Also, cell phone adoption rates and device sophistication are likely driven also by other factors such as landline infrastructure, network technology, disposable income and demographics. Not sure if you’ve seen the TED Talk video with Malcolm Gladwell talking about spaghetti sauce. There’s an interesting story there about plotting results and trying to find an explanation when dots are all over the place.

Thanks Aaron. Great video – I think everyone should check it out:
http://www.ted.com/index.php/talks/malcolm_gladwell_on_spaghetti_sauce.html.

Also, I looked for data on home sizes and found this amazing Web site:
http://www.nationmaster.com
and even a ready-made graph for home size vs. mobile:
http://www.nationmaster.com/plot/peo_siz_of_hou/med_mob_pho/flag

I like the nationmaster site. Humm. Weak correlation eh? At least two possibilities there: my theory is completely wrong, or it needs to be refined. I’m leaning towards the conclusion that all social media and technology adoption patterns need to be assessed within certain boundaries to be meaningful. The reason is that there is a large number of drivers that can determine the adoption outcome, and any single variable will fail to be a good predictor that applies globally. My academic background is in Biology, and I see parallels in trying to explain why, for example, large apes exist in Africa and Asia but not in South America. We may need our own version of Alfred Russel Wallace to examine the geographical patterns for tech adoption

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