Post by Erica Fagen
“Search, Scrape, Clip, Cite.”[i] These are the steps Hate 2.0 collaborator Shawn Graham suggested in his Prezi earlier this year entitled “Digital Tools & Perspectives for New Graduate Students in History.” Both David Cranswick and I used this shorthand in our early research on the Hate 2.0 project. First came “searching” (going through Flickr and various websites), then “scraping” (Outwit Hub Firefox plugin), followed by “clipping” (Evernote) and finally “citing” (Zotero). The subsequent paragraphs will present this process in greater detail as well as the digital humanities methods used to identify the amateur photographers at the centre of our analysis.
When I first started my research on Hate 2.0, Jen suggested that I search through the following websites: the webportal of the Bundesverfassungsschutz or BfV (Federal Office for the Protection of the Constitution), no-nazi.net (an anti-Nazi civil society initiative promoting web literacy for today’s youth), and the web presence of the Amadeu Antonio Stiftung (a foundation named in memory of a victim of right-wing violence). All of these websites were very helpful in familiarizing me with tactics for dealing with neo-Nazism in today”s Germany. Jen also suggested I look at Die Zeit”s newspaper series “Neue deutsche Nazis” (New German Nazis) , where for some time journalists have been compiling special reports on this emerging trend.[ii] It was at this point that I decided I would apply some digital humanities tools. In order to see the common themes in eleven articles in the series which appeared between March 8th to May 16th 2012, I decided to use Voyant Tools to identify which words were most commonly used, as well to see if I could learn anything new from the resulting tag cloud. (I recently re-entered the article information into Voyant, as the link from May was not working).
My initial results were not what I was expecting. Voyant deduced that words like “und” (and), “dem” and “der” (variations of the) were the most common in articles about neo-Nazis. Knowing this was incorrect, I changed the language settings to German and applied so-called stopwords, words like “and,” “a,” and “the.” Instantly, my results were more in line with what I was looking for: words like “Neonazis,” “Rechtextremismus” (right-wing extremism) and “Deutschland” were the most common words in the eleven texts. Other words such as “NPD” and “Dortmund” were less popular, but appeared 66 and 38 times, respectively. The tag cloud can be seen here. Though this exercise was not as useful as I thought it would be, it did confirm that “Rechtsextreme” and “Rechtsextremismus” were popular keywords, and would be useful search terms when mining through Flickr photographs.[iii]
Following this brief experiment with Voyant, I consulted David Cranswick’s work with digital humanities tools. He used Outwit Hub, Evernote, and Zotero. In order to “scrape” material and collect data from the Web, David used the Outwit Hub Firefox plugin. To better understand this process, I ran an exercise in Outwit Hub. Recreating the process of “catching” links, images, and other kinds of data and then exporting it to csv and HTML files, I now understood how David found his information. To read David’s reflection on his digital humanities process, click here and here.
David’s research notes on Evernote proved to be invaluable when searching through the work of these amateur activist photographers. Each photographer had two to five notes which included (if available) their Profile Information, Flickr profile, Twitter profile, Contact Network, and blog/personal website. The entries of Björn Kietzmann, Boeseraltermann, mikael.zellman, neukoellnbild, PM Cheung, Thomas Rassloff, and WildeBilder were among those examined. After reading that PM Cheung and Boeseraltermann were at the core of the network, with Boeseraltermann, an activist dedicated to photographing anti-Nazi themes, and PM Cheung, a highly connected documentarian dedicated to capturing a variety of demonstrations and causes, I turned to their Flickr pages and analyzed their online collection. They did not disappoint — both activists do an excellent job in documenting neo-Nazi rallies and creative forms of anti-Nazi opposition. (One of Boeseraltermann’s photographs can be seen here, one of PM Cheung’s here). Though this work is interesting for a variety of reasons, I decided to look further into the work of photographers who were labeled as “intermediate” within the larger network. When I researched the work of Thomas Rassloff on Flickr, I went through tags dealing with neo-Nazi and anti-Nazi themes such as “Nazidemo,” “Gegenprotest,” “Demo,” and “Rassismus.” Following this, I discovered that Rassloff”s photographs were engaging and imaginative, so I decided that Rassloff’s work would a nice complement to the others for this article.[iv] One photograph of Thomas Rassloff that is particularly intriguing may be seen here.
The styles of the three photographers are different, yet they all have a strong activist tone to their work. The process of selecting them, as well as learning more about mainstream media reports on the rise of neo-Nazism, was greatly aided by the use of digital humanities technologies, without which the selection process would have been much more difficult. Thanks to the process of “Search, Scrape, Clip, Cite,” collecting the vast amounts of information on anti-Nazi activists was an organized, interesting, as well as fun process.
Although we can say with some certainty that they formed part of a network community of anti-Nazi activists, confirmed by the degree of in- and out-group relationality and the mere fact that they comment on each other”s images, our article will explore ways we might gauge their three-way conversation, and its impact in the diverse publics that emerge online as their images are tweeted, tagged, and shared.
[iv] It should be noted here that Jen and I took over this Zotero account, which we now use a citing and bibliographic tool for articles relating to protest, social media, and visual culture. We continue to use the “Cite” step highlighted in the Prezi.