YouTuber "Schlep built a huge following tracking down alleged child predators on Roblox before being kicked off. The platform is facing multiple lawsuits over child safety. Last month, Kentucky attorney general Russell Coleman announced the details of yet another lawsuit against Roblox over suspected pedophiles lurking on the hugely popular gaming platform. While doing so, Coleman singled out the work of one self-described "predator hunter" who claims to have helped identify alleged abusers mixing with young gamers. "Roblox is even trying to silence those who raised these security risks," Coleman said. "The famous case of one of their developers, Schlep, immediately comes to mind." Schlep is in fact Michael, a 22-year-old Texan who has spent the last two years working with a group of other Roblox players to track down and identify people purportedly seeking to groom young children on the platform--predators like the one Schlep says allegedly groomed him a decade ago, which he says led ...

This paper introduces two large-scale multilingual comment datasets, YT-30M (and YT-100K) from YouTube. The analysis in this paper is performed on a smaller sample (YT-100K) of YT-30M. Both the datasets: YT-30M (full) and YT-100K (randomly selected 100K sample from YT-30M) are publicly released for further research. YT-30M (YT-100K) contains 32236173 (108694) comments posted by YouTube channel that belong to YouTube categories. Each comment is associated with a video ID, comment ID, commentor name, commentor channel ID, comment text, upvotes, original channel ID and category of the YouTube channel (e.g., 'News & Politics', 'Science & Technology', etc.).

At first glance at this video, you'd be forgiven for mistaking it as a clip from the latest children's cartoon. But the footage is very much real, and features a real-life robot. Boston Dynamics' robot dog, Spot, can be seen wearing a blue, sparkly dog costume as it performs an impressive dance routine. 'Spot is meeting another strange dog and making friends through the power of dance. Meet Sparkles!' Boston Dynamics said.

A quarter of US adults regularly get their news from YouTube. Yet, despite the massive political content available on the platform, to date no classifier has been proposed to identify the political leaning of YouTube videos. To fill this gap, we propose a novel classifier based on Bert -- a language model from Google -- to classify YouTube videos merely based on their titles into six categories, namely: Far Left, Left, Center, Anti-Woke, Right, and Far Right. We used a public dataset of 10 million YouTube video titles (under various categories) to train and validate the proposed classifier. We compare the classifier against several alternatives that we trained on the same dataset, revealing that our classifier achieves the highest accuracy (75%) and the highest F1 score (77%). To further validate the classification performance, we collect videos from YouTube channels of numerous prominent news agencies, such as Fox News and New York Times, which have widely known political leanings, and apply our classifier to their video titles. For the vast majority of cases, the predicted political leaning matches that of the news agency.

YouTube, a widely popular online platform, has transformed the dynamics of con-tent consumption and interaction for users worldwide. With its extensive range of content crea-tors and viewers, YouTube serves as a hub for video sharing, entertainment, and information dissemination. However, the exponential growth of users and their active engagement on the platform has raised concerns regarding suspicious commenter behaviors, particularly in the com-ment section. This paper presents a social network analysis-based methodology for detecting suspicious commenter mob-like behaviors among YouTube channels and the similarities therein. The method aims to characterize channels based on the level of such behavior and identify com-mon patterns across them. To evaluate the effectiveness of the proposed model, we conducted an analysis of 20 YouTube channels, consisting of 7,782 videos, 294,199 commenters, and 596,982 comments. These channels were specifically selected for propagating false views about the U.S. Military. The analysis revealed significant similarities among the channels, shedding light on the prevalence of suspicious commenter behavior. By understanding these similarities, we contribute to a better understanding of the dynamics of suspicious behavior on YouTube channels, which can inform strategies for addressing and mitigating such behavior.

"You won't believe what's coming," warned the title of a January 2023 video from the Inside China Auto YouTube channel. "Europe's premium car makers aren't ready for this," warned another video from the same channel, uploaded in July. Produced by Shanghai-based automotive journalist Mark Rainford, a former communications executive for Mercedes-Benz, the channel is one of several by China-based Western commentators agog at what they are seeing--and driving. The channels tell salivating viewers that the tech-heavy yet keenly priced Chinese electric vehicles that have appeared on China's domestic market since the end of the global pandemic will soon wipe the floor with their Western counterparts. Auto executives in Europe, America, and Japan "didn't believe China's car companies could grow so fast," Rainford told me. "That's an easy mistake to make from outside the country.

Every week I get dozens of emails about ChatGPT and student education. As a professor of law focused on technology and a mom of three kids I am fielding messages from my kids' schools, from my workplace, and from colleagues near and far. They share a sense of panic about the AI chatbot that is able to almost magically--and instantly--generate schoolwork that students for centuries produced through laborious research and writing. How will students learn to research and write? How will we assess them?

Inrecent years, data science has become an increasingly popular field due to the explosion of data and the need to extract valuable insights from it. While traditional education can be expensive and time-consuming, many aspiring data scientists turn to YouTube to learn the necessary skills. In this article, we've compiled a list of the best YouTube channels for learning data science for free in 2023. We cover a range of topics, including mathematics, programming, data analysis, machine learning and deep learning, career tips and guidance, interview preparation, and staying updated with the latest trends in the field. Whether you're a beginner or an experienced data scientist, these channels can help you improve your skills and knowledge in data science without breaking the bank.

Last week, Ben Shapiro--editor emeritus of the conservative media organization the Daily Wire, prolific right-wing firebrand, and someone who seems to wear a blazer and button-up every day of his life--played a round of Minecraft on his YouTube channel. Often, the sandbox game is about the quiet joys of pastoral life, where players construct homesteads, rear livestock, and grow crops in a world made up entirely of perfectly equilateral cubes. It's also the best-selling game ever, which is why Minecraft videos tend to pop up on the channels of blue-haired Twitch celebrities, not a 39-year old political commentator who initially entered the upper tier of pundit-influencers as an anti-anti-Trump Republican who toured America's college campuses in order to argue with 19-year-olds about Marxism. Yet here he was, in 2023, doing his best to defeat the Ender Dragon for all five and a half million of his subscribers. "I'm still hitting the wrong buttons here, I'm not used to the controls," Shapiro said as he limply gestured his pickaxe toward a stone laden with glowing rubies.

Machine Learning is a rapidly growing field with immense potential to revolutionize various industries. Learning machine learning can be complicated, and we often need help figuring out where to start. With the increasing availability of free resources, we end up spending a lot of time figuring out the best resources to hone our skills. With this in mind, we have compiled a list of the top 15 machine-learning channels that offers valuable insights, tips, and tutorials. Whether you are a beginner looking to gain a solid understanding of the foundations or an expert seeking to deepen your knowledge and stay up to date with the latest trends, these channels will offer a wealth of information from some of the top minds and biggest brands in the community.