New Media and Sentiment Mining

Overview

Do you have a lot of textual data from various sources that comes in fast and furious and 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 participants with necessary skillsets to design sentiment analysis system and apply them in various social fields.

Course Description & Learning Outcomes

At the end of the course, participants will be able to: - Identify where sentiment analysis can be applied - Evaluate and analyse the classification techniques for sentiment classification and apply it with open source libraries - Design a sentiment analysis system for customer feedback and reviews - Design a sentiment analysis system for news and social media for applications in finance - Evaluate and assess sentiment analysis at a granular level for entities and aspects

Recommended Prerequisites

- Participants must successfully completed Text Analytics course offered by NUS-ISS. - Participants must have strong programming skills using python, familiar with packages like Numpy, Pandas, Scikit-Learn, and well versed using virtual environments in python (GitHub or CoLab). - Interested participants who did not take the Text Analytics course offered by NUS-ISS must take a precourse assessment quiz and pass it. The precourse assessment quiz is administered online and tests the participant’s practical understanding of text mining concepts necessary to undertake this course successfully. The assessment does not test programming skills.

Pre-course instructions

- No printed copies of course materials are issued. - Participants must bring their internet-enabled computing device (laptops, tablet etc) with power charger to access and download course materials. Registration close date: 25/10/2023