相关论文: A First Look at Scams on YouTube

Growing evidence suggests that YouTube's recommendation algorithm plays a role in online radicalization via surfacing extreme content. Radical Islamist groups, in particular, have been profiting from the global appeal of YouTube to…

We present a method for accurately predicting the long time popularity of online content from early measurements of user access. Using two content sharing portals, Youtube and Digg, we show that by modeling the accrual of views and votes on…

The rapid growth of YouTube Shorts, now serving over 2 billion monthly users, reflects a global shift toward short-form video as a dominant mode of online content consumption. This study investigates algorithmic bias in YouTube Shorts'…

In this paper, we study the ecosystem of the abused Web Clips in underground economy. Through this study, we find the Web Clips is wildly used by perpetrators to penetrate iOS devices to gain profit. This work starts with 1,800 user…

Social media have been growing rapidly and become essential elements of many people's lives. Meanwhile, social media have also come to be a popular source for identity deception. Many social media identity deception cases have arisen over…

Predicting which specific parts of a video users will replay is important for several applications, including targeted advertisement placement on video platforms and assisting video creators. In this work, we explore whether it is possible…

In the last years, hundreds of new Youtube channels have been creating and sharing videos targeting children, with themes related to animation, superhero movies, comics, etc. Unfortunately, many of these videos are inappropriate for…

Web-based chatbots provide website owners with the benefits of increased sales, immediate response to their customers, and insight into customer behaviour. While Web-based chatbots are getting popular, they have not received much scrutiny…

As more users turn to video-sharing platforms like YouTube as an information source, they may consume misinformation despite their best efforts. In this work, we investigate ways that users can better assess the credibility of videos by…

As tools for content editing mature, and artificial intelligence (AI) based algorithms for synthesizing media grow, the presence of manipulated content across online media is increasing. This phenomenon causes the spread of misinformation,…

The increasing importance of videos as a medium for engagement, communication, and content creation makes them critical for organizations to consider for user feedback. However, sifting through vast amounts of video content on social media…

Understanding the prevalence of misinformation in health topics online can inform public health policies and interventions. However, measuring such misinformation at scale remains a challenge, particularly for high-stakes but understudied…

The recent emergence of machine-manipulated media raises an important societal question: how can we know if a video that we watch is real or fake? In two online studies with 15,016 participants, we present authentic videos and deepfakes and…

In this work, we provide an in-depth analysis of collusive entities on YouTube fostered by various blackmarket services. Following this, we propose models to detect three types of collusive YouTube entities - videos seeking collusive likes,…

This article provides a quantitative analysis of privacy-compromising mechanisms on 1 million popular websites. Findings indicate that nearly 9 in 10 websites leak user data to parties of which the user is likely unaware; more than 6 in 10…

How to tell if a review is real or fake? What does the underworld of fraudulent reviewing look like? Detecting suspicious reviews has become a major issue for many online services. We propose the use of a clique-finding approach to discover…

In this paper, we present a novel problem, namely video timeline modeling. Our objective is to create a video-associated timeline from a set of videos related to a specific topic, thereby facilitating the content and structure understanding…

Online video platforms receive hundreds of hours of uploads every minute, making manual content moderation impossible. Unfortunately, the most vulnerable consumers of malicious video content are children from ages 1-5 whose attention is…

Recommendations algorithms of social media platforms are often criticized for placing users in "rabbit holes" of (increasingly) ideologically biased content. Despite these concerns, prior evidence on this algorithmic radicalization is…

We present the first large-scale measurement study of cross-partisan discussions between liberals and conservatives on YouTube, based on a dataset of 274,241 political videos from 973 channels of US partisan media and 134M comments from…