Text Analytics

Course Description & Learning Outcomes

This course aims to equip you with the knowledge and skills to effectively analyse large amounts of textual data such as customer feedback and social media conversations to discover themes, patterns and trends to aid in improving business process and decision making. In scenario-based case studies, you will be introduced to common text analytics tasks such as data pre-processing and preparation, linguistic/knowledge resources management, concept extraction, text categorisation, clustering, association and trend analysis. You will practise performing these tasks following a well-defined process in hands-on sessions. At the end of the course, participants will be able to: - Identify main themes or topics in the collection of documents or textual data (e.g. the prominent issues customers are complaining about). - Discover relationships and patterns among topics (e.g. which issues tend to co-occur in complaints). - Categorise documents based on discovered topics and user-definable criteria, such as grouping complaints about similar issues for further investigation. - Perform sentiment analysis on customers’ comments, reviews, or other forms of opinions to gain a good sense about how customers feel about their company, products and services. - Extract useful information from text as structured data to enable integration into the traditional data mining process. - Incorporate business understanding and domain knowledge into the analysis through lexical and knowledge resources.