The R Package sentometrics to Compute, Aggregate and Predict with Textual Sentiment
34 Pages Posted: 11 Nov 2017 Last revised: 26 Dec 2018
Date Written: November 9, 2017
We provide a hands-on introduction to optimized textual sentiment indexation using the R package sentometrics. Driven by the need to unlock the potential of textual data, sentiment analysis is increasingly used to capture its information value. The sentometrics package implements an intuitive framework to efficiently compute sentiment scores of numerous texts, to aggregate the scores into multiple time series, and to use these time series to predict other variables. The workflow of the package is illustrated with a built-in corpus of news articles from two major U.S. journals to forecast the VIX index.
Keywords: Penalized Regression, Prediction, R, sentometrics, Textual Sentiment, Time Series
JEL Classification: C10, C32, C49, C52, C87, E37
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