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Full-Text Articles in Engineering
Finding Truth In Fake News: Reverse Plagiarism And Other Models Of Classification, Matthew Przybyla, David Tran, Amber Whelpley, Daniel W. Engels
Finding Truth In Fake News: Reverse Plagiarism And Other Models Of Classification, Matthew Przybyla, David Tran, Amber Whelpley, Daniel W. Engels
SMU Data Science Review
As the digital age creates new ways of spreading news, fake stories are propagated to widen audiences. A majority of people obtain both fake and truthful news without knowing which is which. There is not currently a reliable and efficient method to identify “fake news”. Several ways of detecting fake news have been produced, but the various algorithms have low accuracy of detection and the definition of what makes a news item ‘fake’ remains unclear. In this paper, we propose a new method of detecting on of fake news through comparison to other news items on the same topic, as …
Framework For Evaluation Of Flash Flood Models In Wildfire-Prone Areas, Brian Cunningham, David Benepe, Bryan Cikatz, Evangelos Giakoumakis
Framework For Evaluation Of Flash Flood Models In Wildfire-Prone Areas, Brian Cunningham, David Benepe, Bryan Cikatz, Evangelos Giakoumakis
SMU Data Science Review
Abstract. In this paper, we present an innovative framework for evaluating the increased risk of flash flooding in areas that have been subjected to wildfires. Wildfires cause large-scale damage to an area’s soil and vegetation thus increasing both the likelihood and severity of flash flooding. Utilizing remote sensing to analyze aerial imagery of areas that have been affected by wildfires, we can investigate how much a landscape has changed and how that may adversely affect downstream areas in the event of a flash flooding event. There are currently no established frameworks from which downstream local officials can quickly assess the …