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.
economy Example Dataset (576 articles from Wikinews) for testing.
as.RollingLDA RollingLDA objects used in this package.
getChunks Getter for
RollingLDA Performing the method from scratch.
updateRollingLDA Performing updates on
Rieger, Jonas, Carsten Jentsch and Jörg Rahnenführer (2021). "RollingLDA: An Update Algorithm of Latent Dirichlet Allocation to Construct Consistent Time Series from Textual Data". Accepted for Findings of EMNLP 2021. URL https://www.statistik.tu-dortmund.de/fileadmin/user_upload/Lehrstuehle/IWuS/Forschung/rollinglda.pdf.
Report bugs at https://github.com/JonasRieger/rollinglda/issues
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