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Found 6 papers, 4 papers with code
HLTRI at W-NUT 2020 Shared Task-3: COVID-19 Event Extraction from Twitter Using Multi-Task Hopfield Pooling
Extracting structured knowledge involving self-reported events related to the COVID-19 pandemic from Twitter has the potential to inform surveillance systems that play a critical role in public health.
Identification of Multimodal Stance Towards Frames of Communication
In this paper we introduce MMVax-Stance, a dataset of 11, 300 multimedia documents retrieved from social media, which have stance annotations towards 113 different frames of communication.
From Hesitancy Framings to Vaccine Hesitancy Profiles: A Journey of Stance, Ontological Commitments and Moral Foundations
While billions of COVID-19 vaccines have been administered, too many people remain hesitant.
VaccineLies: A Natural Language Resource for Learning to Recognize Misinformation about the COVID-19 and HPV Vaccines
The ontological commitments of the Misinformation taxonomies provide an understanding of which misinformation themes and concerns dominate the discourse about the two vaccines covered in VaccineLies.
Identifying the Adoption or Rejection of Misinformation Targeting COVID-19 Vaccines in Twitter Discourse
In this paper we describe a novel framework for identifying the stance towards misinformation, relying on attitude consistency and its properties.
Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution
We present a sequence of unsupervised, nonparametric Bayesian models for clustering complex linguistic objects.
