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An integrated framework in R for textual sentiment time series aggregation and prediction

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The current tokenization leaves French elisions attached to their words. This causes some sentiment words to not be identified when computing sentiment. For example, "l'abandon" is not identified as negative...

It always tickles me that compute_sentiment can yield values outside the [-1;1] range when using the "proportionalPol" method. ``` r library(sentometrics) sample_text id word_count LM_sample #> 1: C'est un abandon...

I like tokenizing text by myself before using compute_sentiment. My usual framework is to start from a quanteda::corpus, from which I create a sento_corpus and a quanteda::tokens object. I just...

The result of a cleaning with BFG repo cleaner. The cleaning correct a large number of commits in the past.

Hi, would it be possible to implement a custom aggregation method in the `ctr_agg` function? At the moment my data is quarterly (GDP and PCE). ```r [1] "2000-02-01" "2000-05-01" "2000-08-01"...