WSJ: Pittsburgh Synagogue Shooting Puts Spotlight on Fringe Platforms and Their Partners

A study from the Cyprus University of Technology, the Princeton Center for Theoretical Science and University College London found that 5.4% of all Gab posts include a hate word—more than twice as often as Twitter posts, but much less frequently than on 4chan’s Politically Incorrect message board. The study said popular hashtags on Gab included “Pizzagate,” a conspiracy theory, and “Ban Islam.”

Read the full article: https://www.wsj.com/articles/pittsburgh-synagogue-shootingputs-spotlight-on-fringe-platforms-and-their-partners-1540861173

NY Mag: What We Know About Robert Bowers, the Alleged Pittsburgh Synagogue Shooter

In an article about the shooter in Pittsburgh, New York Magazine referenced NCRI’s analysis as written about in the Washington Post.

Bowers’s racism wasn’t only directed at Jews, the Washington Post reports.

Many of his rants expressed racism against African Americans, according to an analysis of posts gathered by the Network Contagion Research Institute, a group of scientists and engineers who study online hate.

Half a dozen of Bowers’s posts included slurs against women who had relationships with black men. He uploaded many posts that referenced nooses and ropes and hanging. Nearly 20 posts used the n-word.

Read the full article: http://nymag.com/intelligencer/2018/10/what-we-know-about-robert-bowers-alleged-synagogue-shooter.html

UAB research shows ‘explosive growth’ of Antisemitism online and we must confront it

An Alabama.com article references our work and the paper “A Quantitative Approach to Understanding Online Antisemitism”.

New research coming out of the University of Alabama at Birmingham detailing an “explosive growth” of Antisemitism online should be a wake-up call for everyone, particularly after last weekend’s shooting at a Pittsburgh synagogue.

Conservatives should be especially concerned, because even though these uninvited bigots are relatively few, they have indeed glommed on the fringes of our movement and must be shaken off before they do lasting damage.

Read the full article: https://www.al.com/opinion/2018/10/uab-research-shows-explosive-growth-of-antisemitism-online-and-we-must-confront-it.html

Another Washington Post article citing our work

In an article about the Pittsburg shooter, the Post writes:

Bowers’s low profile stands in sharp contrast to feeds on Gab, including the since-deleted account in which a user with Bowers’s name compared Jews to Satan and complained that Trump’s “Make America Great Again” movement cannot succeed so long as Jews “infest” the country.

Many of his rants expressed racism against African Americans, according to an analysis of posts gathered by the Network Contagion Research Institute, a group of scientists and engineers who study online hate.

https://www.washingtonpost.com/nation/2018/10/28/victims-expected-be-named-after-killed-deadliest-attack-jews-us-history/

WHYY: Scientists say Gab, a Philly-based social network, is an incubator of hate

WHYY intervierwed Jeremy, Joel, and Barry about Gab, hate online, social networks, and our work and mission.

Gab launched in 2016 and claims to have more than 800,000 users. The company describes itself as a defender of free speech, an alternative to platforms like Facebook or Twitter it says have become too politically correct. CEO Andrew Torba has argued that efforts to limit “fake news” and offensive content on social media have resulted in censorship.

The site’s claim of being a marketplace for free speech is a facade, said Joel Finkelstein, a neuroscientist at Princeton University. Finkelstein directs the Network Contagion Research Institute, a nonprofit that studies how hate spreads online and includes collaborators in the U.S., the U.K., and Europe.

“It’s very clear that free speech is a coded way of saying the alt-right can say what they want,” Finkelstein said.

Read the full article: https://whyy.org/articles/how-scientists-say-gab-a-philly-based-social-network-became-an-incubator-of-hate/

NCRI Research Featured in the Washington Post

Craig Timberg and Drew Harwell wrote an excellent article about out most recent paper,   “A Quantitative Approach to Understanding Online Antisemitism“.  Their article, “Racism and anti-Semitism surged in corners of the Web after Trump’s election, analysis shows” discusses our finding about the nature of alt-right social networks and how real world events such as Trump’s election, inauguration, and the Charlottesville protests markedly increased anti-black and anti-semitic rhetoric and memes in these networks.   They also explain how hateful memes such as “The Happy Merchant” themed memes are created in alt-right networks and move to more mainstream social networks. Continue reading “NCRI Research Featured in the Washington Post”

A Quantitative Approach to Understanding Online Antisemitism Part 4: Discussion

Main Take-Aways. To summarize, the main take-away points from our quantitative assessment are:

  1. Racial and ethnic slurs are increasing in popularity on fringe Web communities. This trend is particularly notable for antisemitic language.
  2. Our word2vec models in conjunction with graph visualization techniques, demonstrate an explosion in diversity of coded language for racial slurs used in /pol/ and Gab. Our methods demonstrate a means to dissect this language and decode racial discourse on fringe networks.
  3. The use of ethnic and antisemitic terms on Web communities is substantially influenced by real-world events. For instance, our analysis shows a substantial increase in the use of ethnic slurs including the term “jew” around Donald Trump’s Inauguration, while the same applies for the term “white” and the Charlottesville rally.
  4. When it comes to the use of antisemitic memes, we find that /pol/ consistently shares the Happy Merchant Meme, while for Gab we observe an increase in the use in 2017, especially after the Charlottesville rally. Finally, our influence estimation analysis reveals that /pol/ is the most influential actor in the overall spread of the Happy Merchant Memes to other communities in our sample, possibly due to the large volume of Happy merchant memes that are shared within the platform. The Donald however, is the most efficient actor in pushing Happy Merchant memes to all the other sampled Web communities.

Continue reading “A Quantitative Approach to Understanding Online Antisemitism Part 4: Discussion”

A Quantitative Approach to Understanding Online Antisemitism Part 3: Meme Analysis

Disclaimer. Note that content posted on both Web communities can be characterized as highly offensive and racist. In this post, we discuss our analysis without censoring any offensive language, hence we inform the reader that this post contains language that is likely to be upsetting.

 

 

In addition to hateful terms, memes also play a well documented role in the spread of propaganda and ethnic hate in Web communities. To detail how memes spread and how different Web communities influence one another with memes, our previous research established a pipeline which automatically collects, annotates, and analyzes over 160M memes from over 2.6B posts from from Web communities; Reddit, /pol/, Gab, and Twitter. Within Reddit, we pay particular attention to The Donald subreddit (The Donald), a Trump supporting subreddit which notoriously propagates hateful memes and propaganda. In a nutshell, we use perceptual hashing and clustering techniques to track and analyze the propagation of memes across multiple Web communities. Continue reading “A Quantitative Approach to Understanding Online Antisemitism Part 3: Meme Analysis”

A Quantitative Approach to Understanding Online Antisemitism Part 2 : Temporal Analysis

Disclaimer. Note that content posted on both Web communities can be characterized as highly offensive and racist. In this post, we discuss our analysis without censoring any offensive language, hence we inform the reader that this post contains language that is likely to be upsetting.

Our temporal analysis that shows the use of racial slurs over time on Gab and /pol/, our textbased analysis that leverages word2vec embeddings to understand the use of text with respect to ethnic slurs, and our memetic analysis that focuses on the propagation of the antisemitic Happy Merchant meme. Continue reading “A Quantitative Approach to Understanding Online Antisemitism Part 2 : Temporal Analysis”

A Quantitative Approach to Understanding Online Antisemitism : Part 1 Intro

A new wave of growing antisemitism, driven by fringe Web communities, is an increasingly worrying presence in the socio-political realm. The ubiquitous and global nature of the Web has provided tools used by these groups to spread their ideology to the rest of the Internet. Although the study of antisemitism and hate is not new, the scale and rate of change of online data has impacted the efficacy of traditional approaches to measure and understand this worrying trend.

In our latest paper, we present a large-scale, quantitative study of online antisemitism. We collect hundreds of million comments and images from alt-right Web communities like 4chan’s Politically Incorrect board  /pol/) and the Twitter clone, Gab. Using scientifically grounded methods, we quantify the escalation and spread of antisemitic memes and rhetoric across the Web. We find the frequency of antisemitic content greatly increases (in some cases more than doubling) after major political events such as the 2016 US Presidential Election and the “Unite the Right” rally in Charlottesville. Furthermore, this antisemitism appears in tandem with sharp increases in white ethnic nationalist content on the same communities. Continue reading “A Quantitative Approach to Understanding Online Antisemitism : Part 1 Intro”