151 citations · 162 across the 5 of their papers we have counts for
8 papers · 1 filter
Opinions are Made to be Changed: Temporally Adaptive Stance Classification
Rabab Alkhalifa, Elena Kochkina, Arkaitz Zubiaga
Given the rapidly evolving nature of social media and people's views, word usage changes over time. Consequently, the performance of a classifier trained on old textual data can dr…
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…
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…
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…
Cost-Sensitive BERT for Generalisable Sentence Classification with Imbalanced Data
Harish Tayyar Madabushi, Elena Kochkina, Michael Castelle
The automatic identification of propaganda has gained significance in recent years due to technological and social changes in the way news is generated and consumed. That this task…
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…