Megan’s Blog

As Wired recently reported, I have built a large dataset of far-right extremist groups in order to learn about their movement and figure out how they operate so that we can keep our communities safe.

Where does the data come from?

Much of my data comes from public, online sources. For example, despite Facebook claiming to be “no place for hate”, I have found that the Facebook social network is actually a very rich source of data about hate groups and the extreme far-right. For 500,000 members of 1,336 different far-right groups and events, Facebook is the perfect place for recruitment and community-building.

In this blog post, I describe how I divided these 1,336 groups into 11 different far-right extremist ideologies (following the SPLC’s and ADL’s descriptions of these beliefs), and performed some social network data mining to answer questions about group co-membership.

What can we learn from this data?

Since the far-right was attempting to “unite” itself by holding events such as the August 12 Charlottesville rally (recall that this event was literally called “Unite the Right”), I wondered: Do groups from different ideologies share members in common? Which groups have the most members in common? 

What are the different ideologies represented?

I originally had 9 different far-right ideologies in the classification system, and have since expanded to 11, as shown in the table below.

To classify each group or event, I evaluated the text and emojis used the group name and description, as well as text and symbols found in the group cover photo, and the public content if viewable (discussion comments, photos, and so on.)

Primarily, I use Facebook’s own recommendation system for finding new groups (“Suggested Groups”). I also use their search API for groups with keywords and concepts related to a particular ideology.

Special note since some right-wing conspiracy theory web sites are misreporting this fact: Keywords alone are NEVER sufficient to classify groups or to select them for inclusion. With Google now indexing over 620 million Facebook groups, and only 1,336 in my database, obviously I am not just randomly including every group that matches a keyword! That is a ridiculous assertion. For example: “rebel” is a very generic word, and there are many thousands of groups with that word in the title. As explained above, I follow the SPLC’s and ADL’s descriptions, and I manually evaluate every single group for a match. If a group doesn’t clearly qualify (by name, photo, content, and/or description), that group CANNOT be included.

UPDATE: After getting feedback about the way I had classified Christian Identity and The Creativity Movements, I decided to collapse the category, moving Christian Identity into Anti-Semitic as SPLC recommends, and likewise, The Creativity Movement is moved into the Neo-Nazi parent category. This makes a lot more sense. Thank you, readers. I guess I’m back to 11 categories again! Numbers have been updated in the table above.

Social Network Analysis

Below is a diagram (created in Gephi using Fruchterman-Reingold layout) showing co-membership between groups from five of the ideologies: Alt-Right, Neo Confederate, White Nationalist, Anti-Government, and Neo-Nazi. Lines (“edges”) between groups (“nodes”) indicate that the two groups share at least 10 members in common. No group is included if it does not share at least 10 members with another group. Larger nodes mean the group has more members in it.

In the center of the diagram, in purple, is the Unite the Right (UtR) event. Below is a close-up view of the groups and events that had the highest co-membership with UtR. Here I have highlighted the UtR node, and its connected nodes show up with their color (nodes that are disconnected from UtR in this diagram are “greyed out”).

As the diagram shows, UtR not only had a very high number of nodes it shared members with, but the nodes it shared with were from a wide variety of groups from all the other ideologies: Neo-Confederate (red) groups, militias and Oath Keepers (blue), White Nationalist groups (green), Alt-Right groups (yellow), and even Neo-Nazi groups (black).

Which other groups are similarly well-connected? There are a few, but none cast as diverse a net as UtR. The figure below shows some of the largest nodes, all clustered in the busy center of the diagram. We seee a large neo-Confederate group, a very large militia group, a /pol/ (4chan) Alt-Right group, an “anti-SJW” (against “social justice warriors”) group, a “white culture” forum claiming to be the largest on the Internet, an Odinist/Folkish style group, and a forum for National Socialist ideas.

More about classifying groups by primary ideology

The problem of multiple ideologies. Many far-right extremist groups could easily be classified into more than one ideology. Most of these groups are anti-Muslim, misogynist, anti-Semitic, and so on. Therefore, to come up with a group’s primary ideology, I will typically rank the name and description as of higher importance than the cover photo when trying to make the call. Still, there are gray areas. I once saw a group that listed 5 different ethnicities it disliked, used a militia symbol on the cover photo, and had a generic, non-descriptive name. Classifying that group was a challenge.

To handle the multiple-ideology problem early on in this project, I originally developed a tagging system where I could tag groups with multiple keywords. In that system, a group could be classified as “militia / anti-Muslim / folkish” or “neo-Confederate / militia / anti-immigration”. This system quickly became untenable, however. It was just too difficult to generate meaningful graphs when every group could be in multiple categories at once. At this point, I think such a tagging system should be built on top of – or in addition to – a primary classification system.

The problem of changing ideologies. Each time a group changes its name, description, or cover photo, it could change the perception of what the group’s primary ideology is. I have run into a few groups that went from neo-Confederate to militias, from anti-Muslim to anti-Government, from anti-Semitic to Alt-Right, etc.

Combining ideologies.  Depending on the analysis type I want to do, I might sometimes combine some smaller groups into a larger group. For example, if I’m interested in studying “whiteness” groups, I might combine the large white nationalist category with the smaller Christian Identity and racist skinhead categories. However, if I’m specifically studying Christian Identity groups as a niche community, I can keep these ideologies separated.

Over-representation of certain ideologies. Since I live in the southern portion of the United States, I tend to find more Neo-Confederate groups than certain other types of groups that are more prevalent in other areas of the country.

In future blog posts, I’ll show some of my other data sources, as well as other ways to analyze the Facebook data.