This course shows you how to build and test models to assess sentiment in electronic text using SAS Sentiment Analysis Studio.

Learn how to

• build simple and advanced statistical models
• write rules and construct rule-based models
• combine statistical and rule-based models in a hybrid model
• upload models to SAS Sentiment Analysis Server.

Who should attend

System designers, developers, analytical consultants, and linguists who want to understand techniques and approaches for identifying sentiment in textual documents

Formats available	Standard duration
Classroom:	2.0 days

No SAS or programming experience is required. You should be able to log on and off a computer, use a keyboard and mouse, and have a preliminary understanding of the differences between structured (numeric) and unstructured (text) data fields.

This course addresses SAS Text Analytics Common Components, SAS Sentiment Analysis software.

Introduction to SAS Sentiment Analysis

• introduction
• workflow and architecture

Defining the Corpus and Statistical Modeling

• defining a corpus
• building a statistical model
• testing a statistical model

Rule-Based and Hybrid Models

• introduction to rule-based models
• importing learned features and writing CLASSIFIER rules
• building and testing a rule-based model
• writing CONCEPT and REGEX rules
• writing C_CONCEPT, CONCEPT_RULE, and PREDICATE_RULE rules
• building a hybrid model

Working with Sentiment Analysis Server

• uploading models
• configuring Sentiment Analysis Server (self-study)

Sentiment Project Case Study

• case study
• taxonomy structure