An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction

Optimized prediction based on textual sentiment, accounting for the intrinsic challenge that sentiment can be computed and pooled across texts and time in various ways. See Ardia et al. (2018) .


The sentometrics package is an integrated framework for textual sentiment time series aggregation and prediction. It accounts for the intrinsic challenge that, for a given text, sentiment can be computed in many different ways, as well as the large number of possibilities to pool sentiment across texts and time. This additional layer of manipulation does not exist in standard text mining and time series analysis packages. The package therefore integrates the fast qualification of sentiment from texts, the aggregation into different sentiment time series and the optimized prediction based on these measures.

See the project page, the vignette and following paper for respectively a brief and an extensive introduction to the package, and a real-life macroeconomic forecasting application.


To install the package from CRAN, simply do:


The latest development version of sentometrics is available at To install this version (which may contain bugs!), execute:



Please cite sentometrics in publications. Use citation("sentometrics").


This software package originates from a Google Summer of Code 2017 project.


sentometrics 0.5.6

  • new functions: peakdates()
  • modified the purpose of the peakdocs() function and added a peakdates() function to properly handle the entire functionality of extracting peaks
  • a series of documentation fixes

sentometrics 0.5.5

  • new functions: sentiment_bind(), and to_sentiment()
  • defined replacement (of lexicons and names) for a sentolexicons object
  • properly handled lag = 1 in the ctr_agg() function, and set weights to 1 by default for n = 1 in the weights_beta() function
  • solved single failing test for older R version (3.4.4)
  • removed the abind package from Imports
  • removed the zoo package from Imports, by replacing the single occurrence of the zoo::na.locf() function by the fill_NAs() helper function (written in Rcpp)
  • extended the quanteda::docvars() replacement method to a sentocorpus object
  • modified information criterion estimators for edge cases to avoid them turning negative
  • dropped the "x" output element from a sentomodel object (for large samples, this became too memory consuming)
  • dropped the "howWithin" output element from a sentomeasures object, and simplified a sentiment object into a data.table directly instead of a list
  • expanded the do.shrinkage.x argument in the ctr_model() function to a vector argument
  • added a do.lags argument to the attributions() function, to be able to circumvent the most time-consuming part of the computation
  • imposed a check in the sento_measures() function on the uniqueness of the names within and across the lexicons, features and time weighting schemes
  • solved a bug in the measures_merge() function that made full merging not possible
  • the n argument in the peakdocs() function can now also be specified as a quantile

sentometrics 0.5.1

  • minor modifications to resolve few CRAN issues
  • set default value of nCore argument in the compute_sentiment() and ctr_agg() functions to 1
  • classed the output of the compute_sentiment.sentocorpus() function as a sentiment object, and modified the aggregate() function to aggregate.sentiment()

sentometrics 0.5.0

  • new functions: weights_beta(), get_dates(), get_dimensions(), get_measures(), and get_loss_data()
  • renamed following functions: to_global() to measures_global(), perform_agg() to aggregate(), almons() to weights_almon(), exponentials() to weights_exponential(), setup_lexicons() to sento_lexicons(), retrieve_attributions() to attributions(), plot_attributions() to plot.attributions()
  • defunct the ctr_merge() function, so that all merge parameters have to be passed on directly to the measures_merge() function
  • expanded the use of the center and scale arguments in the scale() function
  • added the dateBefore and dateAfter arguments to the measures_fill() function, and dropped NA option of its fill argument
  • added a "beta" time aggregation option (see associated weights_beta() function)
  • corrected update of "attribWeights" element of output sentomeasures object in required measures_xyz() functions
  • added a new attribution dimension ("lags") to the attributions() function, and corrected some edge cases
  • made a slight correction to the information criterion estimators
  • added a lambdas argument to the ctr_model() function, directly passed on to the glmnet::glmnet() function if used
  • omitted do.combine argument in measures_delete() and measures_select() functions to simplify
  • expanded set of unit tests, included a coverage badge, and added covr to Suggests
  • reimplementation (and improved documentation) of the sentiment calculation in the compute_sentiment() function, by writing part of the code in Rcpp relying on RcppParallel (added to Imports); there are now three approaches to computing sentiment (unigrams, bigrams and clusters)
  • replaced the dfm argument in the compute_sentiment() and ctr_agg() functions by a tokens argument, and altered the input and behaviour of the nCore argument in these same two functions
  • switched from the quanteda package to the stringi package for more direct tokenisation
  • trimmed the list_lexicons and list_valence_shifters built-in word lists by keeping only unigrams, and included same trimming procedure in the sento_lexicons() function
  • added a type column "t" to the list_valence_shifters built-in word list, and reset values of the "y" column from 2 to 1.8 and from 0.5 to 0.2
  • updated the epu built-in dataset with the newest available series, up to July 2018
  • corrected the word 'sparesly' to 'sparsely' in list_valence_shifters[["en"]]
  • further shortened project page to the bare essence
  • omitted statement printed ('Compute sentiment... Done.') in the compute_sentiment() function
  • slightly modified print() generic for a sentomeasures object
  • dropped the "tf-idf" option for within-document aggregation in the ctr_agg() function
  • the sento_lexicons() function outputs a sentolexicons object, which the compute_sentiment() function specifically requires as an input; a sentolexicons object also includes a "[" class-preserving extractor function
  • the attributions() function outputs an attributions object; the plot_attribtutions() function is therefore replaced by the plot() generic
  • defunct the perform_MCS() function, but the output of the get_loss_data() function can easily be used as an input to the MCSprocedure() function from the MCS package (discarded from Imports)
  • moved the parallel and doParallel packages to Suggests, as only needed (if enacted) in the sento_model() function
  • sligthly modified appearance of plotting functions, to drop ggthemes from Imports

sentometrics 0.4.0

  • new functions: measures_delete(), nmeasures(), nobs(), and to_sentocorpus()
  • renamed following functions: any xyz_measures() to measures_xyz(), extract_peakdocs() to peakdocs()
  • dropped do.normalizeAlm argument in the ctr_agg() function, but kept in the almons() function
  • inverted order of rows in output of the almons() function to be consistent with Ardia et al. (2017) paper
  • renamed lexicons to list_lexicons, and valence to list_valence_shifters
  • the stats element of a sentomeasures object is now also updated in measures_fill()
  • changed "_eng" to "_en"' in list_lexicons and list_valence_shifters objects, to be in accordance with two-letter ISO language naming
  • changed "valence_language" naming to "language" in list_valence_shifters object
  • the compute_sentiment() function now also accepts a quanteda corpus object and a character vector
  • the add_features() function now also accepts a quanteda corpus object
  • added an nCore argument to the compute_sentiment(), ctr_agg(), and ctr_model() functions to allow for (more straightforward) parallelized computations, and omitted the do.parallel argument in the ctr_model() function
  • added a do.difference argument to the ctr_model() function and expanded the use of the already existing oos argument
  • brought ggplot2 and foreach to Imports

sentometrics 0.3.5

  • faster to_global()
  • set tolower = FALSE of quanteda::dfm() constructor in compute_sentiment()
  • changed intercept argument in ctr_model() to do.intercept for consistency
  • proper checks on values of feature columns in sento_corpus() and add_features()

sentometrics 0.3.0

  • new functions: diff(), extract_peakdocs(), and subset_measures()
  • modified R Depends from 3.4.2 to 3.3.0, and omitted import of sentimentr
  • word count per document now determined based on a separate tokenisation
  • improved valence shifters search (modified incluce_valence() helper function)
  • new option added for within-document aggregation ("proportionalPol")
  • now correct pass-through of dfm argument in ctr_agg()
  • select_measures() simplified, but toSelect argument expanded
  • calculation in to_global() changed (see vignette)
  • improved add_features(): regex and non-binary (between 0 and 1) allowed
  • all texts and lexicons now automatically to lowercase for sentiment calculation
  • (re)translation of built-in lexicons and valence word lists
  • small documentation clarifications and fixes
  • new vignette and run_vignette.R script
  • shortened project page (no code example anymore)

sentometrics 0.2.0

  • first public release

sentometrics 0.1.0

  • Google Summer of Code 2017 "release" (unstable)

Reference manual

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0.5.6 by Samuel Borms, 3 months ago

Report a bug at

Browse source code at

Authors: David Ardia [aut] , Keven Bluteau [aut] , Samuel Borms [aut, cre] , Kris Boudt [aut]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports caret, compiler, foreach, ggplot2, glmnet, ISOweek, quanteda, Rcpp, RcppRoll, RcppParallel, stats, stringi, utils

Depends on data.table

Suggests covr, doParallel, e1071, parallel, randomForest, testthat

Linking to Rcpp, RcppArmadillo, RcppParallel

System requirements: GNU make

See at CRAN