Computes the attributions to predictions for a (given) number of dates at all possible sentiment dimensions, based on the coefficients associated to each sentiment measure, as estimated in the provided model object.
attributions(model, sentomeasures, do.lags = TRUE,
do.normalize = FALSE, refDates = NULL, factor = NULL)a sentomodel or a sentomodeliter object created with sento_model.
the sentomeasures object, as created with sento_measures, used to estimate
the model from the first argument (make sure this is the case!).
a logical, TRUE also computes the attribution to each time lag. For large time lags,
this is time-consuming.
a logical, TRUE divides each element of every attribution vector at a given date by its
L2-norm at that date, normalizing the values between -1 and 1. The document attributions are not normalized.
the dates (as "yyyy-mm-dd") at which attribution is to be performed. These should be between the latest
date available in the input sentomeasures object and the first estimation sample date (that is, model$dates[1]
if model is a sentomodel object). All dates should also be in get_dates(sentomeasures). If
NULL (default), attribution is calculated for all in-sample dates. Ignored if model is a sentomodeliter
object, for which attribution is calculated for all out-of-sample prediction dates.
the factor level as a single character vector for which attribution has to be calculated in
case of (a) multinomial model(s). Ignored for linear and binomial models.
A list of class attributions, with "documents", "lags", "lexicons",
"features" and "time" as dimensions for which aggregation is computed. The last four dimensions are
data.tables having a "date" column and the other columns the different components of the dimension, with
the attributions as values. Document-level attribution is further decomposed into a data.table per date, with
"id", "date" and "attrib" columns. If do.lags = FALSE, the "lags" element is set
to NULL.
See sento_model for an elaborate modelling example including the calculation and plotting of
attributions. The attribution for logistic models is represented in terms of log odds. For binomial models, it is
calculated with respect to the last factor level or factor column. A NULL value for document-level attribution
on a given date means no documents are directly implicated in the associated prediction.