2018
EMNLP
EMNLP 2018
Stance-Taking in Topics Extracted from Vaccine-Related Tweets and Discussion Forum Posts
Abstract
AbstractThe occurrence of stance-taking towards vaccination was measured in documents extracted by topic modelling from two different corpora, one discussion forum corpus and one tweet corpus. For some of the topics extracted, their most closely associated documents contained a proportion of vaccine stance-taking texts that exceeded the corpus average by a large margin. These extracted document sets would, therefore, form a useful resource in a process for computer-assisted analysis of argumentation on the subject of vaccination.
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Interdisciplinary Bridge
— Interdisciplinary and Machine Learning and Natural Language Processing
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Keyword Pioneer
— topic modelling
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio