739 citations · 2.3k across the 35 of their papers we have counts for
38 papers
The Alignment Bottleneck in Decomposition-Based Claim Verification
Mahmud Elahi Akhter, Federico Ruggeri, Iman Munire Bilal +2
Structured claim decomposition is often proposed as a solution for verifying complex, multi-faceted claims, yet empirical results have been inconsistent. We argue that these incons…
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…
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…
A Pipeline for Generating, Annotating and Employing Synthetic Data for Real World Question Answering
Matthew Maufe, James Ravenscroft, Rob Procter +1
Question Answering (QA) is a growing area of research, often used to facilitate the extraction of information from within documents. State-of-the-art QA models are usually pre-trai…
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…
Evaluation of Abstractive Summarisation Models with Machine Translation in Deliberative Processes
M. Arana-Catania, Rob Procter, Yulan He +1
We present work on summarising deliberative processes for non-English languages. Unlike commonly studied datasets, such as news articles, this deliberation dataset reflects difficu…
Citizen Participation and Machine Learning for a Better Democracy
M. Arana-Catania, F. A. Van Lier, Rob Procter +4
The development of democratic systems is a crucial task as confirmed by its selection as one of the Millennium Sustainable Development Goals by the United Nations. In this article,…
Boosting Low-Resource Biomedical QA via Entity-Aware Masking Strategies
Gabriele Pergola, Elena Kochkina, Lin Gui +2
Biomedical question-answering (QA) has gained increased attention for its capability to provide users with high-quality information from a vast scientific literature. Although an i…
CD2CR: Co-reference Resolution Across Documents and Domains
James Ravenscroft, Arie Cattan, Amanda Clare +2
Cross-document co-reference resolution (CDCR) is the task of identifying and linking mentions to entities and concepts across many text documents. Current state-of-the-art models f…
QMUL-SDS @ DIACR-Ita: Evaluating Unsupervised Diachronic Lexical Semantics Classification in Italian
Rabab Alkhalifa, Adam Tsakalidis, Arkaitz Zubiaga +1
In this paper, we present the results and main findings of our system for the DIACR-ITA 2020 Task. Our system focuses on using variations of training sets and different semantic de…
GiBERT: Introducing Linguistic Knowledge into BERT through a Lightweight Gated Injection Method
Nicole Peinelt, Marek Rei, Maria Liakata
Large pre-trained language models such as BERT have been the driving force behind recent improvements across many NLP tasks. However, BERT is only trained to predict missing words…
QMUL-SDS at CheckThat! 2020: Determining COVID-19 Tweet Check-Worthiness Using an Enhanced CT-BERT with Numeric Expressions
Rabab Alkhalifa, Theodore Yoong, Elena Kochkina +2
This paper describes the participation of the QMUL-SDS team for Task 1 of the CLEF 2020 CheckThat! shared task. The purpose of this task is to determine the check-worthiness of twe…
Measuring prominence of scientific work in online news as a proxy for impact
James Ravenscroft, Amanda Clare, Maria Liakata
The impact made by a scientific paper on the work of other academics has many established metrics, including metrics based on citation counts and social media commenting. However,…
Better Early than Late: Fusing Topics with Word Embeddings for Neural Question Paraphrase Identification
Nicole Peinelt, Dong Nguyen, Maria Liakata
Question paraphrase identification is a key task in Community Question Answering (CQA) to determine if an incoming question has been previously asked. Many current models use word…
Estimating predictive uncertainty for rumour verification models
Elena Kochkina, Maria Liakata
The inability to correctly resolve rumours circulating online can have harmful real-world consequences. We present a method for incorporating model and data uncertainty estimates i…
Autoencoding Word Representations through Time for Semantic Change Detection
Adam Tsakalidis, Maria Liakata
Semantic change detection concerns the task of identifying words whose meaning has changed over time. The current state-of-the-art detects the level of semantic change in a word by…
How we do things with words: Analyzing text as social and cultural data
Dong Nguyen, Maria Liakata, Simon DeDeo +4
In this article we describe our experiences with computational text analysis. We hope to achieve three primary goals. First, we aim to shed light on thorny issues not always at the…
RumourEval 2019: Determining Rumour Veracity and Support for Rumours
Genevieve Gorrell, Kalina Bontcheva, Leon Derczynski +3
This is the proposal for RumourEval-2019, which will run in early 2019 as part of that year's SemEval event. Since the first RumourEval shared task in 2017, interest in automated c…
Nowcasting the Stance of Social Media Users in a Sudden Vote: The Case of the Greek Referendum
Adam Tsakalidis, Nikolaos Aletras, Alexandra I. Cristea +1
Modelling user voting intention in social media is an important research area, with applications in analysing electorate behaviour, online political campaigning and advertising. Pr…
Can We Assess Mental Health through Social Media and Smart Devices? Addressing Bias in Methodology and Evaluation
Adam Tsakalidis, Maria Liakata, Theo Damoulas +1
Predicting mental health from smartphone and social media data on a longitudinal basis has recently attracted great interest, with very promising results being reported across many…
All-in-one: Multi-task Learning for Rumour Verification
Elena Kochkina, Maria Liakata, Arkaitz Zubiaga
Automatic resolution of rumours is a challenging task that can be broken down into smaller components that make up a pipeline, including rumour detection, rumour tracking and stanc…
Discourse-Aware Rumour Stance Classification in Social Media Using Sequential Classifiers
Arkaitz Zubiaga, Elena Kochkina, Maria Liakata +5
Rumour stance classification, defined as classifying the stance of specific social media posts into one of supporting, denying, querying or commenting on an earlier post, is becomi…
Urban Analytics: Multiplexed and Dynamic Community Networks
Weisi Guo, Guillem Mosquera Donate, Stephen Law +3
In the past decade, cities have experienced rapid growth, expansion, and changes in their community structure. Many aspects of critical urban infrastructure are closely coupled wit…
Turing at SemEval-2017 Task 8: Sequential Approach to Rumour Stance Classification with Branch-LSTM
Elena Kochkina, Maria Liakata, Isabelle Augenstein
This paper describes team Turing's submission to SemEval 2017 RumourEval: Determining rumour veracity and support for rumours (SemEval 2017 Task 8, Subtask A). Subtask A addresses…