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Data Mining Tools Combat COVID-19 Misinformation, Identify Symptoms


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Artist's conception of drilling down for data.

The algorithm identified three symptoms unique to COVID-19 compared to the flu: ageusia, or loss of the tongues taste function; shortness of breath, and anosmia, or loss of the sense of smell.

Credit: Paul Fleet/Shutterstock

Researchers at the University of California, Riverside (UCR) and the University of Texas Rio Grande Valley developed an algorithm that identified three unique COVID-19 symptoms that are distinct from those of influenza.

The algorithm mined Google Trends data for 2019 and 2020 using nonnegative discriminative analysis to root out terms unique to one dataset compared to the other.

UCR's Jia Chen said, "We assumed that symptom searches in 2019 would lead to influenza or other respiratory ailments, while searches for the same symptoms in 2020 could be either."

UCR’s Jia Chen described the algorithm as potentially easy to incorporate into a tool that might help scientists investigating other diseases learn more about symptoms.

From UC Riverside News
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Abstracts Copyright © 2021 SmithBucklin, Washington, DC, USA


 

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