The
main goal of my team’s project is to see if there is a relationship
between traditional globalization and globalization or participation
on-line for different countries. We hope to see a correlation between
global on-line activity for a country and economic and trade
information, such as GDP per capita.
To
accomplish this goal, we decided to combine three data sources: Alexa,
World Bank, and Wikipedia. Alexa is a site that contains immense
amounts of information about websites in the world. One of the aspects
that we were interested in using, was the top accessed 100 sites for
each country so we could determine how global a country was on-line.
World Bank contains many databases with general data about the world,
but we were interested in the financial and trade information about
countries for globalization off-line information. Thirdly, Wikipedia is
one of the most popular wikis and we used it to get user participation
information.
I
focused on gathering data from Alexa by downloading the web pages with
the top 100 site listings for each country, and then processing them
with python. We wanted to have a global metric that would represent how
global a country was on-line based on its top 100 sites. Figuring out
how to calculate this metric proved to be more complicated than actually
doing the calculation for all of the countries. We first looked at all
of the sites and assigned a global number to each based on the number
of countries that included them in the top 100 sites. Then for each
country, we added up the number for each site it contained in its top
100 sites and got a global metric that we could use to sort the
countries by how global they were.
Another
issue that we weren’t anticipating was receiving different country
names from Alexa and World Bank. We compared and matched each country
name from Alexa to World Bank & our wikipedia data and then used the
country names from Alexa in our actual data.
We
then combined the data from each source together by country. For each
country, the data included the global metric we calculated, the GDP
& GNP per capita (USD & PPP), trade, military, the number of
internet users, and a number representing online participation (from
Wikipedia data).
When
we start graphically analyzing the data, we hope that the global metric
and the GDP, GNP, or trade have a relationship. It would also be
interesting to see whether the countries that have larger military
interests have lower on-line globalization, or participation. The last
thing that would be interesting to see would be if the online
participation rate is directly related to the global metric.
