Related papers: Anonymity and Identity Online

Large Language Models (LLMs) are increasingly deployed in resume screening pipelines. Although explicit PII (e.g., names) is commonly redacted, resumes typically retain subtle sociocultural markers (languages, co-curricular activities,…

Name disambiguation -- a fundamental problem in online academic systems -- is now facing greater challenges with the increasing growth of research papers. For example, on AMiner, an online academic search platform, about 10% of names own…

The exchange of personal information in digital environments poses significant risks, including identity theft, privacy breaches, and data misuse. Addressing these challenges requires a deep understanding of user behavior and mental models…

With the rapid growth of social media usage, a common trend has emerged where users often make sarcastic comments on posts. While sarcasm can sometimes be harmless, it can blur the line with cyberbullying, especially when used in negative…

Dark jargons are benign-looking words that have hidden, sinister meanings and are used by participants of underground forums for illicit behavior. For example, the dark term "rat" is often used in lieu of "Remote Access Trojan". In this…

Subtle and indirect hate speech remains an underexplored challenge in online safety research, particularly when harmful intent is embedded within misleading or manipulative narratives. Existing hate speech datasets primarily capture overt…

Argument mining and stance detection are central to understanding how opinions are formed and contested in online discourse. However, most publicly available resources focus on mainstream platforms such as Twitter and Reddit, leaving…

The goal of this work is to systematically extract information from hacker forums, whose information would be in general described as unstructured: the text of a post is not necessarily following any writing rules. By contrast, many…

Moral dilemmas play an important role in theorizing both about ethical norms and moral psychology. Yet thought experiments borrowed from the philosophical literature often lack the nuances and complexity of real life. We leverage 100,000…

This paper examines the efficacy of utilizing large language models (LLMs) to detect public threats posted online. Amid rising concerns over the spread of threatening rhetoric and advance notices of violence, automated content analysis…

Anonymity forms an integral and important part of our digital life. It enables us to express our true selves without the fear of judgment. In this paper, we investigate the different aspects of anonymity in the social Q&A site Quora. The…

Dark humor often relies on subtle cultural nuances and implicit cues that require contextual reasoning to interpret, posing safety challenges that current static benchmarks fail to capture. To address this, we introduce a novel multimodal,…

Recently, Web forums have been invaded by opinion manipulation trolls. Some trolls try to influence the other users driven by their own convictions, while in other cases they can be organized and paid, e.g., by a political party or a PR…

Now-a-days, derogatory comments are often made by one another, not only in offline environment but also immensely in online environments like social networking websites and online communities. So, an Identification combined with Prevention…

With the recent rise of #MeToo, an increasing number of personal stories about sexual harassment and sexual abuse have been shared online. In order to push forward the fight against such harassment and abuse, we present the task of…

Different entities with the same name can be difficult to distinguish. Handling confusing entity mentions is a crucial skill for language models (LMs). For example, given the question "Where was Michael Jordan educated?" and a set of…

Generative models such as Large Language Models (LLM) and Multimodal Large Language models (MLLMs) trained on massive web corpora can memorize and disclose individuals' confidential and private data, raising legal and ethical concerns.…

With the rise of social media, rumor detection has drawn increasing attention. Although numerous methods have been proposed with the development of rumor classification datasets, they focus on identifying whether a post is a rumor, lacking…

The argument for persistent social media influence campaigns, often funded by malicious entities, is gaining traction. These entities utilize instrumented profiles to disseminate divisive content and disinformation, shaping public…

This paper aims to help structure the risk landscape associated with large-scale Language Models (LMs). In order to foster advances in responsible innovation, an in-depth understanding of the potential risks posed by these models is needed.…