1 citations · 1 across the 10 of their papers we have counts for
12 papers
Misinformation Without Triggers: From Factual Answers to Downstream Decisions
Lin Tian, Marian-Andrei Rizoiu
Language models learn from web documents, some of them false, and false content can reach a model's answer to a factual question and the summaries and decisions that use it. Most d…
Reading Too Much into Context: Passive Exposure Can Steer LLM Decisions
Yuxiang Zheng, Lin Tian, Marian-Andrei Rizoiu
Large language model (LLM) assistants can now search the web and consult external sources while completing user requests. These sources can provide useful evidence, but they can al…
From a Word-Level Dictionary to Sentence-Level Semantics: Multilingual Grievance Labelling with Contextual Models
Lin Tian, Marian-Andrei Rizoiu
Grievance is one of the warning signs analysts look for when assessing threats of violence. It is increasingly measured at scale from online text, most often with word-level lexico…
Long Live Fine-Tuning: Task-Specific Transformers Outperform Zero-Shot LLMs for Misinformation Response Classification on Reddit
JooYoung Lee, Lin Tian, Angela Brillantes +2
As large language models (LLMs) become default tools for online information verification, an implicit assumption follows them: that scale and general capability are sufficient for…
DREAMS: A Social Exchange Theory-Informed Modeling of Misinformation Engagement on Social Media
Lin Tian, Marian-Andrei Rizoiu
Social media engagement prediction is a central challenge in computational social science, particularly for understanding how users interact with misinformation. Existing approache…
Tree of Agents: Improving Long-Context Capabilities of Large Language Models through Multi-Perspective Reasoning
Song Yu, Xiaofei Xu, Ke Deng +2
Large language models (LLMs) face persistent challenges when handling long-context tasks, most notably the lost in the middle issue, where information located in the middle of a lo…
Learning to Make Friends: Coaching LLM Agents toward Emergent Social Ties
Philipp J. Schneider, Lin Tian, Marian-Andrei Rizoiu
Can large language model (LLM) agents reproduce the complex social dynamics that characterize human online behavior -- shaped by homophily, reciprocity, and social validation -- an…
X-Troll: eXplainable Detection of State-Sponsored Information Operations Agents
Lin Tian, Xiuzhen Zhang, Maria Myung-Hee Kim +2
State-sponsored trolls, malicious actors who deploy sophisticated linguistic manipulation in coordinated information campaigns, posing threats to online discourse integrity. While…
Mario at EXIST 2025: A Simple Gateway to Effective Multilingual Sexism Detection
Lin Tian, Johanne R. Trippas, Marian-Andrei Rizoiu
This paper presents our approach to EXIST 2025 Task 1, addressing text-based sexism detection in English and Spanish tweets through hierarchical Low-Rank Adaptation (LoRA) of Llama…
Estimating Online Influence Needs Causal Modeling! Counterfactual Analysis of Social Media Engagement
Lin Tian, Marian-Andrei Rizoiu
Understanding true influence in social media requires distinguishing correlation from causation--particularly when analyzing misinformation spread. While existing approaches focus…
Signals from the Floods: AI-Driven Disaster Analysis through Multi-Source Data Fusion
Xian Gong, Paul X. McCarthy, Lin Tian +1
Massive and diverse web data are increasingly vital for government disaster response, as demonstrated by the 2022 floods in New South Wales (NSW), Australia. This study examines ho…
Before It's Too Late: A State Space Model for the Early Prediction of Misinformation and Disinformation Engagement
Lin Tian, Emily Booth, Francesco Bailo +2
In today's digital age, conspiracies and information campaigns can emerge rapidly and erode social and democratic cohesion. While recent deep learning approaches have made progress…