sentometrics-package: sentometrics: An Integrated Framework for Textual Sentiment...

In sentometrics: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction

Description

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 quantification of sentiment from texts, the aggregation into different sentiment time series and the optimized prediction based on these measures.

Main functions

• Corpus (features) generation: sento_corpus, add_features, as.sento_corpus

• Sentiment computation and aggregation into sentiment measures: ctr_agg, sento_lexicons, compute_sentiment, aggregate.sentiment, as.sentiment, sento_measures, peakdocs, peakdates, aggregate.sento_measures

• Sparse modeling: ctr_model, sento_model

• Prediction and post-modeling analysis: predict.sento_model, attributions

Note

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

Author(s)

Maintainer: Samuel Borms [e-mail] (ORCID)

Authors:

• David Ardia [e-mail] (ORCID)

• Keven Bluteau [e-mail] (ORCID)

• Kris Boudt [e-mail] (ORCID)

Other contributors:

• Jeroen Van Pelt [e-mail] [contributor]

• Andres Algaba [e-mail] [contributor]

References

Ardia, Bluteau, Borms and Boudt (2021). The R Package sentometrics to Compute, Aggregate, and Predict with Textual Sentiment. Journal of Statistical Software 99(2), 1-40, doi: 10.18637/jss.v099.i02.

Ardia, Bluteau and Boudt (2019). Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values. International Journal of Forecasting 35, 1370-1386, doi: 10.1016/j.ijforecast.2018.10.010.

See Also

Useful links:

• https://sentometrics-research.com/sentometrics/

• Report bugs at https://github.com/SentometricsResearch/sentometrics/issues

sentometrics documentation built on Aug. 18, 2021, 9:06 a.m.