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An Ontological Approach to Misinformation: Quickly Finding Relevant Information

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Title: An Ontological Approach to Misinformation: Quickly Finding Relevant Information
Authors: Hicks, Chelsea
Keywords: misinformation
social media
text mining
Issue Date: 04 Jan 2017
Abstract: Identifying misinformation (i.e. rumors) is a growing field of research in the information systems field. This is due to the fact that during recent tragedies (i.e. Boston Bombings, Ebola, etcetera), rumors spread rapidly on social media platforms, which will hide the facts about an event. This results in rumors being spread even more, further hiding the events. In this study, we draw from research from the semantic web to tackle this problem. We propose the use of ontologies and related concepts can help find accurate information for a case quickly and accurately. Combined with a weighting formula, we will be able to display the most relevant results to an interested party. In this research in progress, we outline our plan on how to accomplish this once an ontology and dataset is found.
Pages/Duration: 8 pages
ISBN: 978-0-9981331-0-2
DOI: 10.24251/HICSS.2017.111
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Text Mining in Big Data Analytics Minitrack

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