This online course, “Sentiment Analysis,” is designed to give you an introduction to the algorithms, techniques and software used in sentiment analysis. Their use will be illustrated by reference to existing applications, particularly product reviews and opinion mining. The course will try to make clear both the capabilities and the limitations of these applications. For real-world applications, sentiment analysis draws heavily on work in computational linguistics and text-mining. At the completion of the course, a student will have a good idea of the field of sentiment analysis, the current state-of-the-art and the issues and problems that are likely to be the focus of future systems.
WEEK 1: Introduction and Subjectivity Analysis
- Text Categorization concepts
- Computational Linguistics concepts
- Subjectivity Analysis
WEEK 2: Sentiment Extraction
- Topic Extraction
- Product Reviews
- Sentiment analysis of Comparative Sentences
WEEK 3: Opinion Retrieval and Spam
- Searching for Opinions
- Opinion Summarization
- Opinion Spam
Homework in this course consists of short answer questions to test concepts.
In addition to assigned readings, this course also has supplemental readings available online.
Analysts, researchers and managers who deal with, or might need to deal with, Sentiment Analysis systems at a variety of levels - needs assessment, design, deployment and operation.
ADVANCED / INTERMEDIATE - see prerequisites
prerequisites, you may be able to make do with just one of the two listed above.
Options for Credit and Recognition:
Specializations are an easy way for you to demonstrate mastery of a specific skill in statistics and analytics. This course is part of the Text Mining and Analytics Specialization which gives a deep dive into text mining, natural language processing and sentiment analysis. Requires Python and some familiarity with Bayesian statistics.
All materials will be made available in the course.
To be scheduled.
To be scheduled.
Course Fee: $469
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