11 citations · 27 across the 5 of their papers we have counts for
6 papers
Categorising Fine-to-Coarse Grained Misinformation: An Empirical Study of COVID-19 Infodemic
Ye Jiang, Xingyi Song, Carolina Scarton +2
The spreading COVID-19 misinformation over social media already draws the attention of many researchers. According to Google Scholar, about 26000 COVID-19 related misinformation st…
'A Modern Up-To-Date Laptop' -- Vagueness in Natural Language Queries for Product Search
Andrea Papenmeier, Alfred Sliwa, Dagmar Kern +3
With the rise of voice assistants and an increase in mobile search usage, natural language has become an important query language. So far, most of the current systems are not able…
Uni-DUE Student Team: Tackling fact checking through decomposable attention neural network
Jan Kowollik, Ahmet Aker
In this paper we present our system for the FEVER Challenge. The task of this challenge is to verify claims by extracting information from Wikipedia. Our system has two parts. In t…
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…