Text and Social Media Analytics

Postgraduate | 2026

Course page banner
area/catalogue icon
Area/Catalogue
COMP X300
Course ID icon
Course ID
205854
Level of study
Level of study
Postgraduate
Unit value icon
Unit value
6
Course level icon
Course level
2
Study abroad and student exchange icon
Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
Yes
University-wide elective icon
University-wide elective course
Yes
Single course enrollment
Single course enrolment
Yes
alt
Note:
Course data is interim and subject to change

Course overview

This course provides students an overview of contemporary natural language processing with students gaining hands-on experience implementing NLP with real-world data. This course aims to equip learners with the knowledge and skills to analyse textual datasets. Building upon concepts of data science practice, this course will look at the challenges and methods used for textual datasets. By examining the methods of tokenization, sentiment analysis and topic modelling, the course shows how patterns in textual data can be identified.

Course learning outcomes

  • Demonstrate an ability to read text into R and then prepare it with tokenisation, stop words and word embedding
  • Understand the importance of representative datasets and the ethics of using text from social sources
  • Demonstrate the ability to apply sentiment analysis and topic modelling to real datasets
  • Demonstrate the ability to interpret the output from sentiment analysis and topic modelling

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A