If you use the CorEx topic model, please cite the following paper:
Gallagher, R. J., Reing, K., Kale, D., & Ver Steeg, G. (2017). Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge. Transactions of the Association for Computational Linguistics (TACL), 5, 529-542.
More intuition for the CorEx algorithm is given in these slides, along with additional examples of topic modeling with anchor words.
For a more detailed tutorial of how to run the CorEx topic model in Python, extract information from it, choose the number of topics, and run hierarchical and semi-supervised models, see this Jupyter notebook.