rollinglda-package {rollinglda}

rollinglda: Construct Consistent Time Series from Textual Data

Description

RollingLDA is a rolling version of the Latent Dirichlet Allocation (LDA). By a sequential approach, it enables the construction of LDA-based time series of topics that are consistent with previous states of LDA models. After an initial modeling, updates can be computed efficiently, allowing for real-time monitoring and detection of events or structural breaks.
For bug reports and feature requests please use the issue tracker: https://github.com/JonasRieger/rollinglda/issues. Also have a look at the (detailed) example at https://github.com/JonasRieger/rollinglda.

Data

economy Example Dataset (576 articles from Wikinews) for testing.

Constructor

as.RollingLDA RollingLDA objects used in this package.

Getter

getChunks Getter for RollingLDA objects.

Modeling

RollingLDA Performing the method from scratch.
updateRollingLDA Performing updates on RollingLDA objects.

Author(s)

Maintainer: Jonas Rieger [e-mail] (ORCID)

References

Rieger, Jonas, Carsten Jentsch and Jörg Rahnenführer (2021). "RollingLDA: An Update Algorithm of Latent Dirichlet Allocation to Construct Consistent Time Series from Textual Data". EMNLP Findings 2021. URL doi:10.18653/v1/2021.findings-emnlp.201.

See Also

Useful links:

• https://github.com/JonasRieger/rollinglda

• Report bugs at https://github.com/JonasRieger/rollinglda/issues