activity
20162023
most citedDiscourse-Aware Rumour Stance Classification in Social Media Using Sequential Classifiers

151 citations · 305 across the 14 of their papers we have counts for

collaborators

16 papers

cs.CL2023★ 1 cited

Sig-Networks Toolkit: Signature Networks for Longitudinal Language Modelling

Talia Tseriotou, Ryan Sze-Yin Chan, Adam Tsakalidis +4

We present an open-source, pip installable toolkit, Sig-Networks, the first of its kind for longitudinal language modelling. A central focus is the incorporation of Signature-based…

cs.HC2023★ 2 cited

Some Observations on Fact-Checking Work with Implications for Computational Support

Rob Procter, Miguel Arana-Catania, Yulan He +4

Social media and user-generated content (UGC) have become increasingly important features of journalistic work in a number of different ways. However, the growth of misinformation…

cs.CL2023

PANACEA: An Automated Misinformation Detection System on COVID-19

Runcong Zhao, Miguel Arana-Catania, Lixing Zhu +6

In this demo, we introduce a web-based misinformation detection system PANACEA on COVID-19 related claims, which has two modules, fact-checking and rumour detection. Our fact-check…

cs.CL2022

PHEMEPlus: Enriching Social Media Rumour Verification with External Evidence

John Dougrez-Lewis, Elena Kochkina, M. Arana-Catania +2

Work on social media rumour verification utilises signals from posts, their propagation and users involved. Other lines of work target identifying and fact-checking claims based on…

cs.CL2022

Natural Language Inference with Self-Attention for Veracity Assessment of Pandemic Claims

M. Arana-Catania, Elena Kochkina, Arkaitz Zubiaga +3

We present a comprehensive work on automated veracity assessment from dataset creation to developing novel methods based on Natural Language Inference (NLI), focusing on misinforma…

cs.CL2022

Building for Tomorrow: Assessing the Temporal Persistence of Text Classifiers

Rabab Alkhalifa, Elena Kochkina, Arkaitz Zubiaga

Performance of text classification models tends to drop over time due to changes in data, which limits the lifetime of a pretrained model. Therefore an ability to predict a model's…