Analyzing the Targets of Hate in Online Social Media

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 these troubling trends.In this paper, we present a large-scale, quantitative study of online antisemitism. We collect hundreds of million posts and images from alt-right Web communities like 4chan's Politically Incorrect board (/pol/) and 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. We extract semantic embeddings from our corpus of posts and demonstrate how automated techniques can discover and categorize the use of antisemitic terminology. We additionally examine the prevalence and spread of the antisemitic “Happy Merchant” meme, and in particular how these fringe communities influence its propagation to more mainstream communities like Twitter and Reddit. Taken together, our results provide a data-driven, quantitative framework for understanding online antisemitism. Our methods serve as a framework to augment current qualitative efforts by anti-hate groups, providing new insights into the growth and spread of hate online.

Section: Related Workmentioning

confidence: 99%

A Quantitative Approach to Understanding Online Antisemitism

Zannettou

Finkelstein²,

Bradlyn

et al. 2020

“…Online Hate. Researchers have also studied hate speech on mainstream social networks like Twitter (Silva et al 2016;Mondal, Silva, and Benevenuto 2017;Davidson et al 2017;Olteanu et al 2018), Reddit (Olteanu et al 2018), Facebook (Ben-David andMatamoros-Fernandez 2016), YouTube (Ottoni et al 2018), and Instagram (Hosseinmardi et al 2015). Closer to our work is research on fringe communities in 4chan and Reddit.…”

Section: Related Workmentioning

confidence: 86%

“And We Will Fight for Our Race!” A Measurement Study of Genetic Testing Conversations on Reddit and 4chan

Mittos

Zannettou

Blackburn

et al. 2020

Progress in genomics has enabled the emergence of a booming market for “direct-to-consumer” genetic testing. Nowadays, companies like 23andMe and AncestryDNA provide affordable health, genealogy, and ancestry reports, and have already tested tens of millions of customers. At the same time, alt- and far-right groups have also taken an interest in genetic testing, using them to attack minorities and prove their genetic “purity.” In this paper, we present a measurement study shedding light on how genetic testing is being discussed on Web communities in Reddit and 4chan. We collect 1.3M comments posted over 27 months on the two platforms, using a set of 280 keywords related to genetic testing. We then use NLP and computer vision tools to identify trends, themes, and topics of discussion. Our analysis shows that genetic testing attracts a lot of attention on Reddit and 4chan, with discussions often including highly toxic language expressed through hateful, racist, and misogynistic comments. In particular, on 4chan's politically incorrect board (/pol/), content from genetic testing conversations involves several alt-right personalities and openly antisemitic rhetoric, often conveyed through memes. Finally, we find that discussions build around user groups, from technology enthusiasts to communities promoting fringe political views.

“…These online platforms serve large-scale audiences and offer wideranging opportunities for user expression. Regrettably, hateful opinions incorporating malicious intent can spread especially fast on these platforms, affecting even popular and well-funded social media platforms such as Twitter and YouTube (Mathew et al 2019;Silva et al 2016).…”

Section: Related Work Identifying Online Harassment In Mediamentioning

confidence: 99%

Closing Pandora’s Box on Naver: Toward Ending Cyber Harassment

Kang

Kuo

Großklags

2022

In reaction to the high-profile celebrity suicides of Sulli and Goo Hara in 2019, attributed to cyberbullying, Korea's most popular internet platform Naver introduced a range of self-regulatory measures to curtail targeted hate comments online in 2020. These regulations include removing the entertainment comment section and pseudonymizing users by revealing comment history but maintaining user anonymity. To take a closer look at celebrity cyberbullying and analyze the effects of Naver's novel self-regulatory measures, we collected data about comments and emoticons from Naver News. In the celebrity space, we find that Sulli and Goo Hara indeed received negative comments and expressions using emoticons. However, our analyses of the self-regulatory measures demonstrate that while user interaction on Naver has decreased, the percentage of negative comments has also fallen, showing that Naver's regulations have had favorable effects.