607 citations · 1.6k across the 31 of their papers we have counts for
35 papers
Hostility Detection in UK Politics: A Dataset on Online Abuse Targeting MPs
Mugdha Pandya, Mali Jin, Kalina Bontcheva +1
Numerous politicians use social media platforms, particularly X, to engage with their constituents. This interaction allows constituents to pose questions and offer feedback but al…
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.…
Multistage BiCross encoder for multilingual access to COVID-19 health information
Iknoor Singh, Carolina Scarton, Kalina Bontcheva
The Coronavirus (COVID-19) pandemic has led to a rapidly growing 'infodemic' of health information online. This has motivated the need for accurate semantic search and retrieval of…
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…
The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe
Georg Rehm, Katrin Marheinecke, Stefanie Hegele +44
Multilingualism is a cultural cornerstone of Europe and firmly anchored in the European treaties including full language equality. However, language barriers impacting business, cr…
European Language Grid: An Overview
Georg Rehm, Maria Berger, Ela Elsholz +33
With 24 official EU and many additional languages, multilingualism in Europe and an inclusive Digital Single Market can only be enabled through Language Technologies (LTs). Europea…
Online Abuse toward Candidates during the UK General Election 2019: Working Paper
Genevieve Gorrell, Mehmet E Bakir, Ian Roberts +2
The 2019 UK general election took place against a background of rising online hostility levels toward politicians and concerns about its impact on democracy. We collected 4.2 milli…
Race and Religion in Online Abuse towards UK Politicians: Working Paper
Genevieve Gorrell, Mehmet E. Bakir, Mark A. Greenwood +2
Against a backdrop of tensions related to EU membership, we find levels of online abuse toward UK MPs reach a new high. Race and religion have become pressing topics globally, and…
The evolution of argumentation mining: From models to social media and emerging tools
Anastasios Lytos, Thomas Lagkas, Panagiotis Sarigiannidis +1
Argumentation mining is a rising subject in the computational linguistics domain focusing on extracting structured arguments from natural text, often from unstructured or noisy tex…
Online Abuse of UK MPs from 2015 to 2019: Working Paper
Mark A. Greenwood, Mehmet E. Bakir, Genevieve Gorrell +3
We extend previous work about general election-related abuse of UK MPs with two new time periods, one in late 2018 and the other in early 2019, allowing previous observations to be…
Local Media and Geo-situated Responses to Brexit: A Quantitative Analysis of Twitter, News and Survey Data
Genevieve Gorrell, Mehmet E. Bakir, Luke Temple +5
Societal debates and political outcomes are subject to news and social media influences, which are in turn subject to commercial and other forces. Local press are in decline, creat…
Partisanship, Propaganda and Post-Truth Politics: Quantifying Impact in Online Debate
Genevieve Gorrell, Mehmet E. Bakir, Ian Roberts +3
The recent past has highlighted the influential role of social networks and online media in shaping public debate on current affairs and political issues. This paper is focused on…
Argumentation Mining: Exploiting Multiple Sources and Background Knowledge
Anastasios Lytos, Thomas Lagkas, Panagiotis Sarigiannidis +1
The field of Argumentation Mining has arisen from the need of determining the underlying causes from an expressed opinion and the urgency to develop the established fields of Opini…
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…
Online Abuse of UK MPs in 2015 and 2017: Perpetrators, Targets, and Topics
Genevieve Gorrell, Mark Greenwood, Ian Roberts +2
Concerns have reached the mainstream about how social media are affecting political outcomes. One trajectory for this is the exposure of politicians to online abuse. In this paper…
Helping Crisis Responders Find the Informative Needle in the Tweet Haystack
Leon Derczynski, Kenny Meesters, Kalina Bontcheva +1
Crisis responders are increasingly using social media, data and other digital sources of information to build a situational understanding of a crisis situation in order to design a…
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…
Simple Open Stance Classification for Rumour Analysis
Ahmet Aker, Leon Derczynski, Kalina Bontcheva
Stance classification determines the attitude, or stance, in a (typically short) text. The task has powerful applications, such as the detection of fake news or the automatic extra…
Gold Standard Online Debates Summaries and First Experiments Towards Automatic Summarization of Online Debate Data
Nattapong Sanchan, Ahmet Aker, Kalina Bontcheva
Usage of online textual media is steadily increasing. Daily, more and more news stories, blog posts and scientific articles are added to the online volumes. These are all freely ac…
Automatic Summarization of Online Debates
Nattapong Sanchan, Ahmet Aker, Kalina Bontcheva
Debate summarization is one of the novel and challenging research areas in automatic text summarization which has been largely unexplored. In this paper, we develop a debate summar…