The initial purpose of the Sentiment Analysis and Topic Modeling (SenTop) project was to analyze survey responses for DHS’s Office of the Chief Procurement Officer related to contracting. However, it has evolved to be a general-purpose text analytics solution that can be applied to any domain/area. It also has been tested/used for human resources topics. SenTop is a DHS-developed Python package for performing descriptive text analytics. Specifically, sentiment analysis and topic modeling on free-form, unstructured text. SenTop uses several methods for analyzing text including combining sentiment analyses and topic modeling into a single capability, permitting identification of sentiments per topic and topics per sentiment. Other innovations include the use of polarity and emotion detection, fully automated topic modeling, and multi-model/multi-configuration analyses for automatic model/configuration selection. The code has been established, performs an analysis, and provides a report but it is only accessed and run by one person per customer request.