Mazieres, A. (2016). Georgraphical projection of Google's suggestions diversity. In 3rd GESIS Computational Social Science Winter Symposium.
title = "Georgraphical projection of Google's suggestions diversity",
author = "A. Mazieres",
booktitle = "3rd GESIS Computational Social Science Winter Symposium",
year = "2016"
However, main designs and ideas inherit from a previous project by Antoine Mazières, Samuel Huron and Julien Palard. This former version was based on a different way to collect data (based on TLDs) that seems not available anymore. More importantly, this project could never be put online due to some Google's restrictions that the present version manage to bypass. You can check this former project page here.
Data is collected from an API well described in this blog post. If you are interested to play on your own with such data, you can check the script I used to gather it.
Projecting data on a map
This API allows to get suggestions for different 'hl' parameter which indicated the language used ("Human Language" ?). Zeitgeist Borders associates to each language a list of country where it's official and widely spoken (according to the country's corresponding wikipedia article). This file allows you to see the current state of theses associations. You can also mouseover a language name on the main page to see associated countries being highlighted.
On the left-pan of the app where the list of suggestions appears, each of them is associated with a weight that express both the number of language for which this suggestion appear, and the rank of this suggestion. For each language, the first suggestion get 3 points, the second 2 and the third 1.