739 citations · 2.4k across the 93 of their papers we have counts for
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Supporting Automated Fact-checking across Topics: Similarity-driven Gradual Topic Learning for Claim Detection
Amani S. Abumansour, Arkaitz Zubiaga
Selecting check-worthy claims for fact-checking is considered a crucial part of expediting the fact-checking process by filtering out and ranking the check-worthy claims for being…
Understanding the Effects of Human-written Paraphrases in LLM-generated Text Detection
Hiu Ting Lau, Arkaitz Zubiaga
Natural Language Generation has been rapidly developing with the advent of large language models (LLMs). While their usage has sparked significant attention from the general public…
Cross-Target Stance Detection: A Survey of Techniques, Datasets, and Challenges
Parisa Jamadi Khiabani, Arkaitz Zubiaga
Stance detection is the task of determining the viewpoint expressed in a text towards a given target. A specific direction within the task focuses on cross-target stance detection,…
Applying the Ego Network Model to Cross-Target Stance Detection
Jack Tacchi, Parisa Jamadi Khiabani, Arkaitz Zubiaga +2
Understanding human interactions and social structures is an incredibly important task, especially in such an interconnected world. One task that facilitates this is Stance Detecti…
FactFinders at CheckThat! 2024: Refining Check-worthy Statement Detection with LLMs through Data Pruning
Yufeng Li, Rrubaa Panchendrarajan, Arkaitz Zubiaga
The rapid dissemination of information through social media and the Internet has posed a significant challenge for fact-checking, among others in identifying check-worthy claims th…
HTIM: Hybrid Text-Interaction Modeling for Broadening Political Leaning Inference in Social Media
Joseba Fernandez de Landa, Arkaitz Zubiaga, Rodrigo Agerri
Political leaning can be defined as the inclination of an individual towards certain political orientations that align with their personal beliefs. Political leaning inference has…
Zero-shot Cross-lingual Stance Detection via Adversarial Language Adaptation
Bharathi A, Arkaitz Zubiaga
Stance detection has been widely studied as the task of determining if a social media post is positive, negative or neutral towards a specific issue, such as support towards vaccin…
SocialPET: Socially Informed Pattern Exploiting Training for Few-Shot Stance Detection in Social Media
Parisa Jamadi Khiabani, Arkaitz Zubiaga
Stance detection, as the task of determining the viewpoint of a social media post towards a target as 'favor' or 'against', has been understudied in the challenging yet realistic s…
ID-XCB: Data-independent Debiasing for Fair and Accurate Transformer-based Cyberbullying Detection
Peiling Yi, Arkaitz Zubiaga
Swear words are a common proxy to collect datasets with cyberbullying incidents. Our focus is on measuring and mitigating biases derived from spurious associations between swear wo…
MAPLE: Micro Analysis of Pairwise Language Evolution for Few-Shot Claim Verification
Xia Zeng, Arkaitz Zubiaga
Claim verification is an essential step in the automated fact-checking pipeline which assesses the veracity of a claim against a piece of evidence. In this work, we explore the pot…
Synergizing Machine Learning & Symbolic Methods: A Survey on Hybrid Approaches to Natural Language Processing
Rrubaa Panchendrarajan, Arkaitz Zubiaga
The advancement of machine learning and symbolic approaches have underscored their strengths and weaknesses in Natural Language Processing (NLP). While machine learning approaches…
Claim Detection for Automated Fact-checking: A Survey on Monolingual, Multilingual and Cross-Lingual Research
Rrubaa Panchendrarajan, Arkaitz Zubiaga
Automated fact-checking has drawn considerable attention over the past few decades due to the increase in the diffusion of misinformation on online platforms. This is often carried…
Cross-lingual Offensive Language Detection: A Systematic Review of Datasets, Transfer Approaches and Challenges
Aiqi Jiang, Arkaitz Zubiaga
The growing prevalence and rapid evolution of offensive language in social media amplify the complexities of detection, particularly highlighting the challenges in identifying such…