151 citations · 325 across the 11 of their papers we have counts for
23 papers
On the Impact of Temporal Concept Drift on Model Explanations
Zhixue Zhao, George Chrysostomou, Kalina Bontcheva +1
Explanation faithfulness of model predictions in natural language processing is typically evaluated on held-out data from the same temporal distribution as the training data (i.e.…
Toxic Language Detection in Social Media for Brazilian Portuguese: New Dataset and Multilingual Analysis
João A. Leite, Diego F. Silva, Kalina Bontcheva +1
Hate speech and toxic comments are a common concern of social media platform users. Although these comments are, fortunately, the minority in these platforms, they are still capabl…
Measuring What Counts: The case of Rumour Stance Classification
Carolina Scarton, Diego F. Silva, Kalina Bontcheva
Stance classification can be a powerful tool for understanding whether and which users believe in online rumours. The task aims to automatically predict the stance of replies towar…
MP Twitter Abuse in the Age of COVID-19: White Paper
Genevieve Gorrell, Tracie Farrell, Kalina Bontcheva
As COVID-19 sweeps the globe, outcomes depend on effective relationships between the public and decision-makers. In the UK there were uncivil tweets to MPs about perceived UK tardi…
Classification Aware Neural Topic Model and its Application on a New COVID-19 Disinformation Corpus
Xingyi Song, Johann Petrak, Ye Jiang +3
The explosion of disinformation accompanying the COVID-19 pandemic has overloaded fact-checkers and media worldwide, and brought a new major challenge to government responses world…
Towards an Interoperable Ecosystem of AI and LT Platforms: A Roadmap for the Implementation of Different Levels of Interoperability
Georg Rehm, Dimitrios Galanis, Penny Labropoulou +21
With regard to the wider area of AI/LT platform interoperability, we concentrate on two core aspects: (1) cross-platform search and discovery of resources and services; (2) composi…