Classifying Vaccine Misinformation in Online Social Media Videos using Natural Language Processing and Machine Learning

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dc.contributor.authorSchmidt, Sarah
dc.contributor.authorThoms, Brian
dc.contributor.authorEryilmaz, Evren
dc.contributor.authorIsaacs, Jason
dc.date.accessioned2023-12-26T18:42:17Z
dc.date.available2023-12-26T18:42:17Z
dc.date.issued2024-01-03
dc.identifier.doihttps://doi.org/10.24251/HICSS.2024.464
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.other5d927a45-7b4a-4aae-8a4e-36f70c669fff
dc.identifier.urihttps://hdl.handle.net/10125/106847
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectSocia Media and Healthcare Technology
dc.subjectmachine learning
dc.subjectmisinformation detection
dc.subjectnatural language processing
dc.subjectsentiment analysis
dc.titleClassifying Vaccine Misinformation in Online Social Media Videos using Natural Language Processing and Machine Learning
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractThe spread of information through online social media videos is one of the most popular ways to share and obtain information, while at the same time the spread of misinformation across these same social spaces has become a significant concern affecting human well-being. Being able to detect this misinformation before it spreads is becoming more and more desirable for many social media platforms. This research focuses on exploring the accuracy of detecting misinformation across two social media platforms, YouTube and BitChute. This involves the classification of video data into two types: genuine information or misinformation. More specifically, this research generates additional metadata embedded within online videos related to the COVID-19 vaccination. Using natural language processing (NLP) we extract medical subject headings (MeSH) terms from video transcripts and classify videos using four machine learning techniques including naïve Bayes, random forest, support vector machine, and logistic regression. Implementation of each classifier is presented, and the accuracy of each technique is compared and discussed.
dcterms.extent10 pages
prism.startingpage3847

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