Far-right extremist women on Facebook

I wrote this little paper after being frustrated at the lack of data about precisely how many women were in far-right groups these days, especially online. I was hearing estimates ranging between 7% and 56%, and some of these didn’t take social media into account at all, but were just back-of-the-envelope guesstimates based on event attendance or interviews with group members.

In this work, I use a very large collection of data I collected about far-right extremist group members from Facebook’s API during the period June 20, 2017 – March 31, 2018. I then used two “genderizer” software packages to infer the gender of these 700,000 extremist group members. I then divide those into ten different ideologies and look for evidence of women’s auxiliaries, sometimes mockingly called “wheat fields”.

Gender of first names of right-wing extremist Facebook users, by ideology

I find that wheat fields DO exist in five of the ten ideologies. The tall spikes at the left side of each graph below represent groups with a super-majority of women, and which are designed to be women-oriented groups.

I find that women’s leadership rates in the Facebook groups differ between ideologies. One smaller ideology, Neo-Nazi, tends to use women in leadership roles at a higher-than-expected rate. White nationalist and Proud Boys, both ideologies with wheat fields for women (a.k.a. women’s auxiliaries) don’t tend to have women in leadership roles in groups as a whole.

Finally, just like in the 1920s with the WKKK (Women’s KKK) and the Ladies’ Memorial Associations (LMAs) and United Daughters of the Confederacy (UDC) I find a systematic marginalization and oppression of women on the one hand comes into conflict with a practical need to leverage women’s networks and organizational abilities on the other hand.

Read “Which way to the wheat field? Women of the radical right on Facebook” here.

Anti-Muslim Networks on Facebook

My work on understanding social networks of anti-Muslim groups on Facebook will be published in the proceedings of the 10th International Conference on Social Informatics (SocInfo 2018). The work will be presented on September 26 in St. Petersburg, Russia.

This research was also recently covered in Buzzfeed News.

Below is a network diagram showing some of the extremist groups and ideologies in my data set, and how they overlap in membership.

Network of Anti-Muslim & other extremist groups on Facebook, with 10+ members in common (click to enlarge)

Two of the key anti-Muslim groups in this network – each scoring very high on betweenness centrality measures – are Infidel Brotherhood International and Stop the Islamization of America. Each of their ego graphs are shown below:

Anti-Muslim groups attract the same audiences as other extremist ideologies, including secessionist neo-Confederates, militant anti-government conspiracy theorists, and racist white nationalists. In addition, groups like IBI and SOIA can serve as a convenient lingua franca: their brand of hate is a common denominator that ties extremists of disparate ideologies together.

Updated Facebook co-membership graphs

I’ve updated the Facebook co-membership graphs (see original post) for my upcoming talk at the International Conference on Computational Social Science (IC2S2) to be held at Northwestern University in July. (extended abstract – PDF)

This talk will include data through the end of March, 2018.

Once again, larger nodes = more people. Closer placement between nodes on the graph mean more folks in common.

What do we learn? There are some ideologies that are woven much more naturally into the fabric of a “united” far-right, as opposed to other ideologies, which will be harder to integrate.

Upcoming work will look at groups with nativist ideologies, including anti-Muslim, anti-Immigrant, and how those correspond to Anti-Government/Patriot/Militia and White Nationalist beliefs.

 

Google Map of Campus Hate Fliers

Background

There have been numerous media stories recounting all the hate group fliers found on university campuses recently. I decided to record these incidents on a Google Map.

UPDATE 1: We are now up to 130 incidents. I continue to update this map, so if I’m missing incidents, tweet them to me @MeganSquire0 or email them to me.

UPDATE 2: There are now 185 campuses on the map, all cited and color-coded.

UPDATE 3: 220 campuses now and the story was amplified this week with the “It’s ok to be white campaign” (Newsweek coverage)

UPDATE 4: I created a separate map to track 2018 incidents

The Map

Data sources

Each map “pin” shows which group did the flyering, as well as the link for where I learned of it. These links are usually tweets from the groups themselves or tweets from students who found the flyers. Sometimes I also use news articles, for example from ViceInside Higher EdUSA TodayNPR, and I also have Google News alerts set up for the alt-right groups so when the flyering incidents are picked up in local media, I get those as well.

A Spotter’s Guide to the Alt-Right

Here is a presentation I gave to UNC students and community members last night about A Spotter’s Guide to Signs & Symbols of the Alt-Right, as it exists in 2017. The focus is on local events and those that I have personal familiarity with (e.g. Charlottesville).

A most heartfelt thanks to everyone who supplied photos for this presentation – I could not have made this without their diligence and beautiful camera work.

Found and liberated 2,151 missing DHS files

On January 18, 2017 the US Department of Homeland Security discontinued its Daily Open Source Infrastructure Report service which it had run since October 2006. To enable researchers to study the content of these reports, I collected as many as I could find (2,151 PDF files) and released them to the Internet Archive. You can find them here: DHS Daily Open Source Infrastructure Reports 2006-2017

The PDF files came from the following URLs:

  • https://www.dhs.gov/sites/default/files/publications/
  • https://www.dhs.gov/sites/default/files/publications/nppd/ip/daily-report/
  • https://www.dhs.gov/xlibrary/assets/

And when these yielded 404 errors (which they did for most pre-2013 files) I used the Internet Archive itself, with the following URL base:

http://web.archive.org/web/20061101153326/https://www.dhs.gov/xlibrary/assets/[filename]

Files are named as they were upon download, in one of the following patterns:

  • DHS_Daily_Report_2006-10-11.pdf (most 2006-2012 files have this format)
  • DHS-Daily-Report-2012-12-06.pdf (a single December 2012 file has this format)
  • dhs-daily-report-2013-01-09 (most 2013-2017 files have this format)

If you are interested in missing dates (for example Archive.org was missing some dates and a few files were corrupted), this blog might be able to help fill in the gaps.

 

Changes to Professor Watchlist – who was removed?

Nearly 12,000 professors have used the AAUP’s “Add My Name” feature in order to be added to Turning Point USA’s Professor Watchlist, and large groups of faculty from Trinity University and University of Notre Dame, among others, have also requested to join. The Professor Watchlist was created in order to expose professors who “advance a radical agenda in lecture halls” and inclusion on the list is supposed to be based on “incidents that have already been reported by a credible source.”

How has the list changed?

The Professor Watchlist debuted in November with 146 names, and has grown to 166 names as of January 3, 2016. I was curious who has been added (obviously not all 12,000 who requested to be added!), and even more curious about who has been taken off the list.

So I created a Google Spreadsheet showing the names in November and the names as they show up in January. I got the November list from archive.org’s Wayback Machine, and the current list from the Professor Watchlist website.

Google Spreadsheet showing additions & removals

Data cleaning steps

  • I re-alphabetized 4 names that were out of order on the November list
  • I lined up the names so we could more easily see who was added/removed
  • I colorized each name with red if it was removed since November, and green if it was added since November.

Findings

Unfortunately, the Wayback Machine does not have the original PW pages indexed for each individual professor, so I can’t go back and see what they wrote for each, but based on what I was able to find online, the rationales for these seven seem very flimsy.

Anyway, at a rate of only 35 changes in a month, Turning Point is going to hire some more interns to enter all these 12,000 names! Good luck with that.

Analysis of the latest 1000 Facebook posts by the Times-News (Aug-Dec)

I was playing around with some code today from Mastering Social Media Mining with Python (by Marco Bonzanini, and published by the same company that published my last two books), and I came up with this snazzy set of scripts (postGetter.py, fileParser.py) that mines the last X posts from any public Facebook page, creates a clickable FB url for each, sorts them in order of most interactions (shares + likes), and creates a spreadsheet with the results.

Here are the results when run for the last 1000 posts by the Times-News of Burlington, our local newspaper: timesNews.csv.

Findings?

Not that surprising or shocking, but here goes. The last 1000 only goes back to August or so (modify the params at the top of the code to make it scrape more), but the top five posts for August-December based on interactions seem to be:

  1. The death of Tim-Bob from Graham Cinema
  2. The abduction of a middle schooler from a bus stop
  3. Kmart closing
  4. 25-minute Christmas Lights show on Maple Ridge Dr.
  5. Housing emergency at Burlington Animal Services

No election-related or weather-related items cracked the top 20.