Twitter penetration in the Netherlands

Credits: Michiel Berger (@michielb), Anne Helmond (@silvertje), Marvin de Reuver (@marvindereuver), Esther Weltevrede (@esthr) and Ton Wesseling (@tonwesseling)

This final image has been made with the help from Ton Wesseling who calculated the percentage of Twitter users per city, using data about the number of inhabitants per city from CBS (January 2010).

Looking at the Twitter penetration per city in the top 25 we see that Amsterdam retains its #1 position with an estimate of 3,78% of the population having a Twitter account while some other major cities drop in ranking (Rotterdam from 2 > 6 and Den Haag from 4 > 13).

In this new view we see some cities climbing (eg. Groningen #2 – 2,99% , Hilversum #4 – 1,89%, – Zwolle #5- 1,67%) and others declining (Rotterdam #6- 1,66% , Eindhoven #12- 1,45%, Den Haag #13 – 1,31%). Many of the cities that climb in the ranking are student cities like Groningen, Zwolle, Leiden, Leeuwarden, Delft and Maastricht.

Thank you Ton!

Download a hi-resolution map on our project website for beautifying your office.

Map updated on January 22: Added Apeldoorn (# 21 in absolute ranking and no longer in the top 25 for relative ranking) and fixed an error in the relative ranking row. Map needs more updating concerning bubble size.

Relative Twitter density in the Netherlands

Credits: Michiel Berger (@michielb), Anne Helmond (@silvertje), Marvin de Reuver (@marvindereuver), Esther Weltevrede (@esthr)

This the second map of the Dutch Twitter population according to the Twittergids data. In the first part I visualized the top 25 Twitter cities in the Netherlands. In this follow-up image Esther Weltevrede and I looked into the relative number of Twitter users per 1000 inhabitants for each province. Color density is relative to the highest penetration (province of North Holland).

What is striking is that the province of Groningen has a relatively high number of Twitter users per 1000 inhabitants.

Hi-resolution images available here.

Top 25 Twitter cities in the Netherlands

Credits: Michiel Berger (@michielb), Anne Helmond (@silvertje), Marvin de Reuver (@marvindereuver), Esther Weltevrede (@esthr)

A few days ago Marvin Reuver and I received data about the number of Twitter users per city in the Netherlands from Michiel Berger from the Twittergids. The Twittergids contains 238,000 registered Twitter users in the Netherlands as of January 14, 2011. I then visualized this information with my Digital Methods Initiative colleague Esther where we focused on the top 25 cities represented in the Twittergids.

As you can see the Provinces of Zeeland and Drenthe are not represented in the top 25. Another interesting finding in the data is that users from the Provinces of Friesland and Limburg often associate themselves with the provinces and not with particular cities.

Download a hi-resolution map on our project website for beautifying your office.

Update: map updated on January 20, numbers 65-80 did not show the correct numbers.

Today, during the New Media course for the first year students at the University of Amsterdam we discussed ‘Citizen Journalism’ (Flew 2008) and ‘From Blogs to Open News: Notes towards a Taxonomy of P2P Publications.’ (Bruns 2003). Concepts such as gatewatching, gatekeeping and open news were central to their assignment.

I asked them to look at the online news models presented by Bruns (2003) and Deuze (2003) to use as a starting point to create their own online news models. They had to try and place the following news sites in their own models:

• http://geenstijl.nl/
• http://buurtlink.nl/
• http://nujij.nl/
• http://news.google.nl/
• http://blufftontoday.com/

It proved to be a very effective and efficient method to discuss the characteristics of each of the news sites.

This post is a follow-up on ‘Walled Garden: Communities and Networks post Web 2.0 (part 1)‘

After discussing the various features of walled gardens, we formed groups and focused on one of the three project topics. Our team took a special interest in the semi-permeability and the root systems and feeds of the walled gardens. How do we measure the permeability of sites?

Characteristics of the permeability of a site include whether the site provides an API, embed code, widget, rss, e-mail, share/this button.

One of the ways to visualize the outcomes of our discussions goals concerning dataflows in (semi-permeable) walled gardens is to make a blueprint. Initial sketch:

The following image is a visualization of Walled Garden Data Flows / Characterizing the types of Web 2.0 data flows between three applications: Facebook, Twitter and Flickr. Walled Garden, 2008 by the Digital Methods Initiative.

Analysis by Anne Helmond, Sabine Niederer, Auke Touwslager, Laura van der Vlies, Esther Weltevrede. Visualization by Auke Touwslager. © 2008.

As a case study we also attempted to map the data flows of my SNS web data. Please note that this map is far from accurate and complete, it is an initial sketch.

First (unfinished) draft in Illustrator:

A question that arises from data flowing from one site to another is what happens if one person moves with the data? For example, does the Creative Commons license change or disappear?

The Recalling RFID seminar on Friday was nicely complemented by workshops on Saturday. With the Digital Methods Initiative we conducted research on various aspects of RFID on the web which resulted in five different projects. I worked on a project titled “RFID Imagery: ‘Wet’ and ‘Dry’ Associations Compared” with Esther Weltevrede, Laura van der Vlies and Richard Rogers. We researched how “wet” (as inspired by Timothy Weaver, University of Denver) the RFID imagery is according to Google.

Our findings are that the RFID imagery is very dry as as associations to the biological are limited (for example human tagging, animal chip implants, etc.) Associations with machines and machinic diagrams predominate as only eight out of the 100 results are wet. I visualized these findings in the following graphics:

click images to enlarge

More details on the project, the research method and the findings can be found on the Digital Methods Initiative wiki.