In a world where ICE agents are shooting US citizens on the street, the need for militias and extremist groups like the Proud Boys to support far-right interests has evaporated. Whether it was protesting Covid lockdowns, attending school board meetings, or facing off against Black Lives Matter protesters, the far-right Proud Boys were always on hand to support Donald Trump's first term in office. When Trump left office in 2021, the group's leaders languished in jail for their role in the January 6 attack on the Capitol. With reported infighting destabilizing the movement, it looked like the group's glory days were behind it. But Trump's return a year ago, and his release of all January 6 prisoners, signaled that a Proud Boy comeback could be in the cards.

Far-right extremists are using livestream gaming platforms to target and radicalise teenage players, a report has warned. The new research, published in the journal Frontiers in Psychology, reveals how a range of extremist groups and individuals use platforms that allow users to chat and livestream while playing video games to recruit and radicalise vulnerable users, mainly young males. UK crime and counter-terror agencies have urged parents to be especially alert to online offenders targeting youngsters during the summer holidays. In an unprecedented move, last week Counter Terrorism Policing, MI5 and the National Crime Agency issued a joint warning to parents and carers that online offenders "will exploit the school holidays to engage in criminal acts with young people when they know less support is readily available". Dr William Allchorn, a senior research fellow at Anglia Ruskin University's international policing and public protection research institute, who carried out the study with his colleague Dr Elisa Orofino, said "gaming-adjacent" platforms were being used as "digital playgrounds" for extremist activity.

The proliferation of ideological movements into extremist factions via social media has become a global concern. While radicalization has been studied extensively within the context of specific ideologies, our ability to accurately characterize extremism in more generalizable terms remains underdeveloped. In this paper, we propose a novel method for extracting and analyzing extremist discourse across a range of online community forums. By focusing on verbal behavioral signatures of extremist traits, we develop a framework for quantifying extremism at both user and community levels. Our research identifies 11 distinct factors, which we term ``The Extremist Eleven,'' as a generalized psychosocial model of extremism. Applying our method to various online communities, we demonstrate an ability to characterize ideologically diverse communities across the 11 extremist traits. We demonstrate the power of this method by analyzing user histories from members of the incel community. We find that our framework accurately predicts which users join the incel community up to 10 months before their actual entry with an AUC of $>0.6$, steadily increasing to AUC ~0.9 three to four months before the event. Further, we find that upon entry into an extremist forum, the users tend to maintain their level of extremism within the community, while still remaining distinguishable from the general online discourse. Our findings contribute to the study of extremism by introducing a more holistic, cross-ideological approach that transcends traditional, trait-specific models.

Group interactions take place within a particular socio-temporal context, which should be taken into account when modelling communities. We propose a method for jointly modelling community structure and language over time, and apply it in the context of extremist anti-women online groups (collectively known as the manosphere). Our model derives temporally grounded embeddings for words and users, which evolve over the training window. We show that this approach outperforms prior models which lacked one of these components (i.e. not incorporating social structure, or using static word embeddings). Using these embeddings, we investigate the evolution of users and words within these communities in three ways: (i) we model a user as a sequence of embeddings and forecast their affinity groups beyond the training window, (ii) we illustrate how word evolution is useful in the context of temporal events, and (iii) we characterise the propensity for violent language within subgroups of the manosphere.

Extremist groups have begun to experiment with artificial intelligence, and in particular generative AI, in order to create a flood of new propaganda. Experts now fear the growing use of generative AI tools by these groups will overturn the work Big Tech has done in recent years to keep their content off the internet. "Our biggest concern is that if terrorists start using gen AI to manipulate imagery at scale, this could well destroy hash-sharing as a solution," Adam Hadley, the executive director of Tech Against Terrorism, tells WIRED. "This is a massive risk." For years, Big Tech platforms have worked hard to create databases of known violent extremist content, known as hashing databases, which are shared across platforms to quickly and automatically remove such content from the internet.

With the rapid growth of Web 3.0 – defined as a decentralised form of the Internet where people have complete control over their own data, more transparency, and far more content accessible to users – human communication will become far easier. Technologies that will facilitate this change include the combination of machine learning, artificial intelligence, and blockchain that will be central pillars of the third version of the Internet. The metaverse, therefore – is a product of Web 3.0, incorporating emerging technologies including augmented reality and allowing users to spend far more time in a virtual world where they can live, work, play, and worship. EMAN has been increasing its focus on the role of extremism in tech and how hate speech and online extremism will evolve as the Internet undergoes significant changes as we know it today. Despite the fact that these metaverses act as efficient socialising tools, global companies are already adapting themselves to this concept by developing new business visions that simulate this new Internet innovation.

We're sure you've heard the claim that "data is the new oil". Web scraping is the process of mining data from the World Wide Web for a specific purpose. In the most simple form, it is copying and pasting a specific set of information to a local database for archival use, scientific analysis, or some other use. Some of the most widely used examples include aggregator websites which provide price comparisons for online goods. There are also sites like archive.orgthat

We've seen no strong evidence of misuse so far They are going against their own word, but nevertheless, it's nice to see that they are releasing everything. EDIT: The unicorn example added below from https://talktotransformer.com/, which has already been updated with the newest 1.5B parameters model. Input: In a shocking finding, scientist discovered a herd of unicorns living in a remote, previously unexplored valley, in the Andes Mountains. Even more surprising to the researchers was the fact that the unicorns spoke perfect English. Output: While there are only a few documented instances of unicorns in the wild, the researchers said the finding proves that there are still large numbers of wild unicorns that remain to be studied.

MOGADISHU, Somalia – U.S. forces say they have carried out three drone strikes within 24 hours in Somalia, stepping up their campaign against the Islamic extremist rebels of al-Shabab and the Islamic State group. The strikes by unmanned drones killed several extremist fighters, a spokeswoman for the U.S. military command in Africa told The Associated Press Sunday. With these three attacks, the U.S. has now carried out 26 attacks in Somalia against extremist targets in 2017, she said. The latest U.S. strikes were carried out in coordination with Somalia's government, she said. The first strike happened Saturday at approximately 4:30 p.m. local Somalia time and it killed one fighter for the extremists group, al-Shabab, said a U.S. Africa command statement.

The United States military said Saturday it has carried out a new drone strike against the Shabab extremist group in Somalia, killing "several" militants. A statement by the U.S. Africa Command said the strike was carried out Friday night in Lower Shabelle region, about 20 miles north of the capital, Mogadishu. It came a day after another strike in the Bay Region, about 100 miles west of Mogadishu. Friday's airstrike was the 23rd the U.S. military has carried out this year against the Al Qaeda-linked Shabab and the far smaller Islamic State group in Somalia. The Trump administration earlier this year approved expanded military operations against extremists in the Horn of Africa nation. The latest U.S. drone strike was carried out in coordination with Somalia's government, the U.S. statement said.