Esther Weltevrede: “The Globalisation Machine. Reinterpreting engine results”

Society of the Query

Lecture by Esther Weltevrede
As a follow up on Martin’s talk, I am going to present some empirical works. These project concern comparing engine results and customization of location. The aim of this study is:

1) Building on Googlization theory and search engine critique.
2) Empirical study. Reinterpreting Google for localization studies.

The key question is: What type of globalization machine is Google?
In this light, a couple of cases will be presented. Weltevrede starts by posing that PageRank is Googles way into the information environment. In an article published in 1998/1999 (?) PageRank is mentioned as the global ranking system for all pages, specifically designed for all the info of the world. Although Google states that they use a large number of variables, PageRank is primarily based on the link. The question of this research is: When Google moves to the local, what happens to the local results? What if we look at some services that are local:

A case:
Google “Amsterdam” and you get (respectively) red light, airport, coffee shops. This same query in returns another set of results (arena, forest, tournament). Local domain Google is another method of localization (e.g. There are 157 local Googles. The key variables are (as far as can be distilled: Google is not very transparent in providing this information):

  • IP address
  • top level domain
  • webmasters page

If you visit one of these Googles (say,, you can also select pages from that locale (only provide me with result from Belgium, for instance). If you select this option, you get local results according to Google. Also, we notice that this particular Google is recommended in three languages (French, Dutch and German, in this case). Another way that Google returns local results is via ‘region” and of course a yellow-page kind of search is offered via Google maps. In answering what we can say about the type of machine Google is, Weltevrede states that it thinks globally and acts locally.

The first case study:
Local and international information sources. Research question: to what extend can the local domain Google present local results? Method used: query all the national Googles in their official languages. Then, in Google Translate, the search term is translated. The second step is to geo- locate sources. Instead of choosing for host, we looked at registration of the website. This is a more precise indication of who owns the website. The top ten results for the query “human rights”.

A picture is shows about the results. The selected national Google is Canada:

map canada

This map indicates that Canada has relatively many local results for ‘human rights’. We can also look at what the top results are globally. The UN is by far the largest source in the list. When we looked at the results more closely, the declaration of human rights keeps popping up. Often websites have translated the declaration in all languages they all call upon this source (On e can interpret this as a way of SEO) .

Next, a ranked tag cloud is shown.
We looked at these sources and blue- tagged sources contain the declaration of human rights. Next, a rank list of all countries queried is given. 40 % of all national Googles do not get any local results. If you look at the type list, you see that Europe leads the list, while at the lower end it is mostly African and Middle- Eastern countries. We can see that the local domain does not mean that you receive local information sources. How then are local results defined? Is it maybe language? A search is done on all Arabic countries. This shows a language web – a shared language space. Does that mean that there are no local sources? In Lebanon, the term “human rights” again is queried. While this does return results, these results do not make it to the top. Local sources are on the second page and beyond.

In order to test this claim (language) we looked at a geographical regions defined by languages: Europe is chosen due to its local and distinct languages. The visual below shows they have very local sources (Again indicated by black domain names). The EU- Googles hardly share sources – characterized by their local sources. This can be argued as a being a language web.


We now move to the last example: comparing two Portuguese speaking sources. Portugal compared to Brazil: Here we might conclude that the established local sources are privileged. Language webs prefer over local webs.

weltevrede_hr_Brazil_mappa weltevrede_hr_Portugal_mappa

Search engine literacy (2nd case study)
We can use Google to read society; we have a particular way of interpreting search engine results. One example method: reading domain names and their main issues. Again, the example of human rights is used here. If we query this, we see a very established result list, where sources are relatively fixed. What happens when we query for a more dynamic topic? In this case a query is done on RFID in 2004;  back then, this was a young space. We see sources competing for the top. Compared to the human rights space, it has rather young and technology-minded sites; the build- up of the list is really different. Another method for research is to look at issues returned:


A third case study:
A query for “rights’ is performed. What is the top ten list of rights per country? The total list as shown. This research required reading and interpreting languages by the team members. The top ten of prominent rights in local domains were collected and visualized. The total image is shown.
The color code – blue rights are shared, while the black ones are culturally specific for domains.

If we zoom in, we see that in Italy, the unique rights are the right to forger and the right to nationality. In Japan, they have computer programming rights, for instance. In Australia, you have specifically man’s rights One favorite: Finland’s every-mans right to freedom to roam in nature. If we are to draw conclusion from this case study, they would be: the globalizing machine can show the shared as well as the locally specific. Google is localizing, regional, nation and local, showing shared and specific. Local results does not mean local sources. Also, different regions on the web are offered, mostly via language.

For more information, see and Digital Methods Initiative. DMI Project page on The Nationality of Issues. Repurposing Google for Internet Research.