EVADE: Exploring Vaccine Dissenting Discourse on TwitterDownload PDF

Published: 30 Jul 2022, Last Modified: 17 May 2023KDD 2022 Workshop epiDAMIK OralReaders: Everyone
Keywords: Social media data analysis, Misinformation, Vaccination dissenting, COVID-19, Classification
Abstract: Social media plays a pivotal role in acquiring, exchanging and expressing public opinions and perceptions on a unprecedented scale in these pandemic times. In this paper, we develop an end-to-end knowledge extraction and management framework named as EVADE. This framework is used to automatically extract information consistent and inconsistent with scientific evidence regarding vaccination. Additionally, we seek to explore public opinion towards vaccination resistance proposing novel natural language processing methods. The knowledge extraction pipeline consists of three major modules, namely, knowledge-base construction, categorization of vaccine dissenting tweets, and effective analyses of discourses in those tweets effectively. Our major contributions lie in the fact that (i) the proposed knowledge extraction framework does not require huge amounts of labelled tweets of different categories and (ii) our module outperformed baselines by a significant margin of ≈ 8% to ≈ 14% in the classification tasks, and effectively analyze vaccine dissenting discourse
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