The past ten years have shown an increase in our use of social media to keep up to date on instances of intolerance. Essentially making it easier to track racism, sexism or anti-semitism used on social media (Facebook, Twitter, Tumblr, etc.). While technology and social media have begun to consume our lives about every day tasks or politics, they are also making it easier to voice opinions and propel prejudiced views.
The print project will narrow into instances of anti-semitism that have been collected from social media sites. I will use the tool, Vouyant Tools, to help track buzzwords linked to anti-semitism. This will help to group together instances that include Trump and the Holocaust in one particular event. Another example will show how many times the phrase ‘Jewish/Jews’ shows up in political talk.
The print project will also include background information on tracking intolerance online. These situations can include where people have participated in intolerances via Facebook or Twitter, or intolerances that are projected via online news outlets. Such instances include the tracking of racism on social media. The twitter project, which was conducted in Canada, followed a series of racist tweets over a 3 month period by using certain terms and hashtags.[1] The use of social media sites, such as Twitter, have been able to trace targeted comments displaying instances of sexism, racism and anti-semitism. Background information of this project will look at the trends of what is now being termed as “Cyber Racism” as defined in Jessie Daniels’ work.[2] This relatively new historiography is looking at how intolerance and prejudice finds a new home in cyber-spaces. For this project, most of the “cyber racism” will be looking specifically at anti-semitism. We have seen a spike of prejudice in recent politics and buzzwords, like ‘anti-semitism, racism, Charlottesville, Trump’ will help to link how prevalent intolerance is being spread through a faster form of communication.
Within in the print project I would like to include a mapping component. This will be shown on geographic categories, split regionally in the United States. The mapping of each region will have corresponding tags of what each incident is organized under. This will demonstrate to readers where incidents related to the Trump administration have surfaced or where incidents have occurred on university campuses. The project will also pull from primary sources of anti-semitism during the most well-known anti-semitic event, the build-up to and the Holocaust.
This project will nicely combine a new historiography of cyber racism but centered around instances of anti-semitism.
[1] “The Twitter Racism Project” Published 2012. Accessed February 12th, 2018 https://www.twitterracism.com
[2] Jessie Daniels, Cyber Racism: White Supremacy Online and the New Attack on Civil Rights. Rowman & Littlefield Publishers. 2009.
Southern Poverty Law Center. Accessed February 13th, 2018. https://www.splcenter.org/hate-map (this was not cited in my post but I feel that it’s important to have here)
This is a great area to be thinking about for a study. The way the web and social media function as tools for hate groups remains significantly understudied. My biggest initial comment is that it would be important to get into the ways that this study engages with notions of the past, memory and history. I think that is going to be evident throughout the space, but just being explicit about that is important. What makes this a digital history project is that you would focus in some way on how notions of the past play out in these discourses.
There are some substantive challenges for doing this kind of work in terms of 1) how to get the data and 2) how to work with and analyze it.
Specifically, collecting social media data is challenging, it generally becomes inaccessible rather quickly and you need to use specific tools to be able to get at the data. For context Documenting the Now is building tools for this kind of work http://www.docnow.io/ and Social Feed Manager is another one https://gwu-libraries.github.io/sfm-ui/
A related challenge in this area, is that you can very rapidly get massive amounts of social media data from these sources. At that point, it becomes challenging to parse that data and make sense of it.
With all of that noted, I think there are likely ways that you could do this work without trying to do massive computational approaches. That is, if you wanted to instead focus on more close reading approaches to parse the ways that anti-semitism works online I think you are likely to find all kinds of interesting insights. In that vein, I think a lot of the methods and approaches that Jessie Daniels uses to analyze sites are likely to be of use for you if you think about going forward with this project.