Iknoor Singh
University of Sheffield
15 Papers
7 Citations
Iknoor Singh is an academic researcher from University of Sheffield. The author has contributed to research in topics: Computer science & Semantic search. The author has an hindex of 3, co-authored 10 publications. Previous affiliations of Iknoor Singh include Panjab University, Chandigarh & University Institute of Engineering and Technology, Panjab University.
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Papers
Classification aware neural topic model for COVID-19 disinformation categorisation.
Xingyi Song,Johann Petrak,Johann Petrak,Ye Jiang,Iknoor Singh,Iknoor Singh,Diana Maynard,Kalina Bontcheva +7 more
TL;DR: The currently largest available manually annotated COVID-19 disinformation category dataset is presented; and a classification-aware neural topic model (CANTM) that combines classification and topic modelling under a variational autoencoder framework is demonstrated.
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On the Coherence of Fake News Articles
Iknoor Singh,Deepak P,Anoop K +2 more
TL;DR: While the relative coherence shortfall of fake news articles as compared to legitimate ones form the main observation from this study, several aspects of the differences are analyzed and outline potential avenues of further inquiry.
On the Coherence of Fake News Articles
Iknoor Singh,Deepak P,Anoop K +2 more
- 14 Sep 2020
TL;DR: This article analyzed the textual coherence of fake news articles vis-a-vis legitimate ones and developed three computational formulations of text coherence drawing upon the state-of-the-art methods in natural language processing and data science.
UTDRM: unsupervised method for training debunked-narrative retrieval models
TL;DR: The experiments show that UTDRM tends to match or exceed the performance of state-of-the-art methods on seven datasets, which demonstrates its effectiveness and broad applicability.
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The False COVID-19 Narratives That Keep Being Debunked: A Spatiotemporal Analysis
TL;DR: In this paper, a spatiotemporal analysis reveals that similar or nearly duplicate false COVID-19 narratives have been spreading in multifarious modalities on various social media platforms in different countries.
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