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In order to identify the words and phrases (ie, n-grams) that are the most likely to appear with COVID-19–related mentions, we used NLP methods to represent each text day (ie, the days that text messages were sent) as a vector of word counts. These vectors were then transformed into term frequency-inverse document frequency (TF-IDF) values. In this study, TF-IDF values were used to identify changes in word use frequency over time.
JMIR Form Res 2021;5(2):e26190
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