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Meta-learning aims to learn a model that can handle multiple tasks generated from an unknown but shared distribution. However, typical meta-learning algorithms have assumed the tasks to be similar such that a single meta-learner is…
Visual social media platforms have become primary venues for political discourse, yet we know little about how moralization operates differently across platforms and topics. Analyzing 2,027,595 TikToks and 1,126,972 Instagram posts during…
Who is the US President? The answer changes depending on when the question is asked. While large language models (LLMs) are evaluated on various reasoning tasks, they often miss a crucial dimension: time. In real-world scenarios, the…
Large Language Models (LLMs) have demonstrated significant potential in medical Question Answering (QA), yet they remain prone to hallucinations and ungrounded reasoning, limiting their reliability in high-stakes clinical scenarios. While…
The ability to detect coordinated activity in communication networks is an ongoing challenge. Prior approaches emphasize considering any activity exceeding a specific threshold of similarity to be coordinated. However, identifying such a…
Large language models (LLMs) are increasingly applied in mental health support systems, where reliable recognition of high-risk states such as suicidal ideation and self-harm is safety-critical. However, existing evaluations primarily rely…
Retrieval-Augmented Generation (RAG) has emerged as a powerful paradigm for Large Language Models (LLMs) to address knowledge-intensive queries requiring domain-specific or up-to-date information. To handle complex multi-hop questions that…
Social networks are vital for information sharing, especially in the health sector for discussing diseases and treatments. These platforms, however, often feature posts as brief texts, posing challenges for Artificial Intelligence (AI) in…
As recent events have demonstrated, disinformation spread through social networks can have dire political, economic and social consequences. Detecting disinformation must inevitably rely on the structure of the network, on users…
Large language models (LLMs) incorporated with Retrieval-Augmented Generation (RAG) have demonstrated powerful capabilities in generating counterspeech against misinformation. However, current studies rely on limited evidence and offer less…
Social media have become a rich source of data, particularly in health research. Yet, the use of such data raises significant ethical questions about the need for the informed consent of those being studied. Consent mechanisms, if even…
Seeking dietary guidance often requires navigating complex professional knowledge while accommodating individual health conditions. Knowledge Graphs (KGs) offer structured and interpretable nutritional information, whereas Large Language…
Social media expose millions of users every day to information campaigns --- some emerging organically from grassroots activity, others sustained by advertising or other coordinated efforts. These campaigns contribute to the shaping of…
Visual content on social media has become increasingly influential in shaping political discourse and civic engagement, but it also limits participation due to the increased cost of multimedia production. In tandem, the growth of generative…
Background: Twitter has become the "wild-west" of marketing and promotional strategies for advertisement agencies. Electronic cigarettes have been heavily marketed across Twitter feeds, offering discounts, "kid-friendly" flavors,…
Understanding how online narratives travel through coalitions is critical for identifying information disorder, yet computational analyses often rely on conservative network constructions that erase initially sparse but salient signals.…
Suicide remains a pressing global public health concern. While social media platforms offer opportunities for early risk detection through online conversation trees, existing approaches face two major limitations: (1) They rely on…
Text-based conversational agents (CAs) are increasingly used in mental health, yet evaluation practices remain fragmented. We conducted a PRISMA-guided systematic review (May-June 2024) across ACM Digital Library, Scopus, and PsycINFO. From…
COVID-19 pandemic has generated what public health officials called an infodemic of misinformation. As social distancing and stay-at-home orders came into effect, many turned to social media for socializing. This increase in social media…
The United States spends nearly 17% of GDP on healthcare yet continues to face uneven access and outcomes. This well-known trade-off among cost, quality, and access - the "iron triangle" - motivates a system-level redesign. This paper…