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A Topic Modeling Analysis of ABC News Articles on Education Matters

Primary supervisor

Guanliang Chen

News media plays an important role in modern society by delivering important information to the public and shaping their opinions with respect to different matters. This project aims to capture and analyze topics covered in the ABC news articles related to education matters in Australia with the aid of topic modeling techniques. These topics may include impact of COVID-19 on learning and teaching, increase of international students in higher education, social and emotional wellbeing of aboriginal students, and so on. Gaining an in-depth understanding of the attention of news media paid to these topics over time is beneficial for us to understand the development progress and status of the Australian education ecosystem.

Student cohort

Double Semester

Aim/outline

Specifically, this project involves:

  1. Collecting news articles on education matters from ABC news, which are available at: https://www.abc.net.au/news/topic/education
  2. Applying a Hierarchical Topic Modeling method (https://github.com/kmpoon/hlta) to identify thematic topics covered in the collected news articles and further analyze their changes (i.e., the number of news articles related to a specific topic) over time.
  3. Interpreting the analysis results and discuss its implications.

Required knowledge

  • Strong programming skills (e.g., Python)
  • Basic knowledge in Data Science, Natural Language Processing, and Machine Learning
  • The following can be a plus: (i) good at academic writing; and (ii) strong motivation in pursing a quality academic publication.