New Media and Sentiment Mining
About This Course
Do you have a lot of textual data from various sources like customers, internal documents, emails, news articles and the social media that comes in fast and furious? Do you want to extract meaningful opinions and sentiments from these textual data automatically?
This course further extends the knowledge and skillsets built by the Text Analytics course. It equips the attendee with the necessary skillsets to design sentiment analysis system and apply them in various social fields.
The ability to process and analyse voluminous textual data provides the participants an edge in this new media age. The objective of this course is to introduce participants to sentiment analysis and its applications. Participants will gain the requisite skills to evaluate the supervised learning algorithms for sentiment classification. They will be able to evaluate and analyse granular meaning of texts from documents and articles.
The course will assume that the participants have good knowledge of text analytics and techniques, and some hands on experience of modelling using these techniques using Python. Participants are also expected to have knowledge of statistics at the level of the Statistics Bootcamp course.
What You'll Learn
� Overview of related tasks of NLP to sentiment analysis
� Supervised learning classification algorithms for sentiment analysis
� Entity and aspect mining for sentiment analysis
� Sentiment visualization tools
� Applications of sentiment analysis to customer analytics and financial applications
� Sentiment analysis and its psychological basis
Entry Requirements
Please see course weblink for more information