Dynamic Topic Modeling was added to iLCM as another form of analysis.

Brief Summary

Classical topic models allow to discover unsupervised topics in document collections and to examine these topics and their distribution within the texts. Dynamic Topic Models (DTM) extended this approach by an additional temporal component. Thus, the changes of topics at different time periods can now be modeled and examined in detail. Especially for large diachronic data sets, this approach represents an exciting extension.

Screenshots

topic evolution in 4 time periods

validation of found topics