Norris’ dimensionality of web features on political party websites tested

When analysing the data on web campagining of the EP elections of 2009, I re-analysed the data Pippa Norris was so kind to let me use. My intention was to show the need for testing on multi-dimensionality of a set of indicators. Originally I intended to include the following in the article about EP web campaigning (Vergeer, Hermans & Cunha, 2013), but this was a classic case of ‘killing your darlings’, because the article became too long.
Norris distinguished the two dimensions of Information and Communication a priori, while I wasn’t sure when reviewing the indicators. Some of the indicators didn’t seem to fit the dimensions. For instance, the search function is seen as an indication for communication, whereas this automated feature might also be included to measure informing. To see whether there is different view on the set of indicators, I performed a multiple correspondence analysis (i.e. multivariate cross tabulation (cf. Greenacre, 2007). This resulted in a different dimensional structure. The slide shows that only a small number of web features indicators compose a single dimension[i]. The remaining indicators do not show significant (co-)variance for a second dimension.

Interpreting the dimension shows us that it refers to the presence (right from the origin) and absence of specific web features (left from the origin): the more to the right the more features political parties have on their websites. The second finding is that looking at the labels C (for communication) and I (for information; cf. Norris 2001) these features are randomly scattered across the dimension. This suggests that web features that were assigned to two different dimensions should be merged according to the correspondence analysis. More close inspection also suggests that these features refer to enabling the website visitor to enlist to participate in parties’ activities.
Below the horizontal line, so-called passive variables are presented for descriptive purposes[ii]. Looking at which parties score low or high on the degree of enabling people to participate, we see that it is in particular a) the major and the minor (and not the fringe parties), b) the Green, extreme left, and conservative parties that offer these features more than average. In particular, the liberals and the center parties show below average presence of participation web features.

Greenacre, M. J. (2007). Correspondence analysis in practice. Boca Raton, Fla. ; London: Chapman & Hall/CRC.
Norris, P. (2001). Digital Divide? Civic Engagement, Information Poverty and the Internet Worldwide. Cambridge: Cambridge University Press.
Vergeer, M., Hermans, L., & Cunha, C. (2013). Web campaigning in the 2009 European Parliament elections: A cross-national comparative analysis. New Media & Society, 15(1), 128–148.

[i] Eigen value = 6.560, Inertia = .205, Cronbach’s α = .875.
‘C’ and ‘I’ indicate the original communication and Information functions as distinguished by Norris (2001).
Categories above the horizontal line belong to variables that influence the dimensional structure. The categories below the horizontal line are supplemental variables that do not influence the dimensionality and are merely included for descriptive purposes.
[ii] Supplementary variables do not influence the dimensionality which arises on the from the analysis on web features (cf. Greenacre, 2007).


Program Course Social Media Theory and Data in Journalism and Political Communication

In an earlier post I announced my new and upcoming course Social Media Theory and Data in Journalism and Political Communication in the Radboud Summer School. This current post presents the general schedule of the course. In short, the morning sessions focus on theories about social media in political communication and journalism. The afternoon sessions are hands-on sessions  on data collection, and data analysis. The afternoon sessions will particularly focus on what you can and can not do with social media data, although I do think you can do a lot more that you might think initially. You will also perform analysis yourself. The main tool will for social media analysis will be R. Why? In short, it’s free, flexible, has specific packages for social media data, works on Windows, Apple and Linux computers and in the cloud (if you want to). There are many more advantages and of course some disadvantages (there’s no perfect software package). I am working on a blog-post about R as a tool for analysis, so stay alert for a new post.

Regarding the afternoon hands-on sessions, I already have several English language social media data sets available for empirical analysis. These are tweet data, profile data as well as social network data.

DAY 1 (AUGUST 1, 2016)

  • Kick-off meeting of the course


  • Introduction to social media, theory and data
  • Presentation of student’s project interests

DAY 2 (AUGUST 2, 2016)

  • Approaches to studying social media data in journalism and political communication


  • The collection of social media data: API’s and software tools
  • Empirical descriptions and visualization of social media data
  • Approaches to longitudinal analysis of social media data

DAY 3 (AUGUST 3, 2016)

  • Social media content analysis: theory and methods
  • Content analysis: political and news issues, sentiment analysis


  • Different approaches to analyzing social media content data
  • Analyzing social media content

DAY 4 (AUGUST 4, 2016)

  • Social network analysis on social media data
  • Different approaches to networks on social media: social relations, hyperlinks, retweets and texts


  • Analyzing social networks and communication networks on social media

DAY 5 (AUGUST 5, 2016)

  • Advanced approaches to analyzing social media data
  • Setting the agenda for social media research in journalism and political communication


  • Student presentations
  • Reflection

Further general information about the Radboud Summer School can be found here.

New publication on social media and social movements in South Korea

Late December 2015 our chapter Voicing Discontent in South Korea. Origins and Channels of Online Civic Movements by Se Jung Park and myself was published in The Routledge Companion to Social Media and Politics and edited by Axel Bruns, Gunn Enli, Eli Skogerbø, Anders Olof Larsson, and Christian Christensen. The edited book consists of a large and diverse collection on social media and politics.

Our chapter consists of three sections. The first section “South Korea’s Path to Wealth and Democracy” is a brief look into South Korea’s recent history of developing into a democracy and economic prosperity driven by Korea’s technology industry (cf. Samsung, LG). The second section focuses on the distinct Korean Web culture and its fast Internet infrastructure. The third section focuses on the sociopolitical relations in South Korea’s collectivist culture. Using World Values Survey data we compare South Korea to other countries, in terms of confidence in political institutions such as parliament and government, civil services, and political parties. In the following section three cases on social movements and social media are presented: Candlelight protests, citizen journalism: OhmyNews, and Gangjeong Movement. The subsequent section focuses on Internet regulation and Election Laws in South Korea, followed by the conclusion.

A big thank you to the editors for inviting to contribute and a special big thank you to Nicki Hall, the project coördinator, for managing this project. More information about the book can be found on the publisher’s website Routledge and on Amazon.

Below are some pictures of a 2008 Candlelight protest that turned violent, the Sewol Candlelight protest of 2014 as well as some videos of recent protests (November 2015) against president Park Geun-hye’s policies. Although these protests are violent, according to experts (mentioned in the first video) South Korea is in a transition to peaceful rallying.