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cs.CL2026

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…

cs.CL2026

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…