SGIA40K15: Natural Language Processing for Public Policy

• None

• SGIA49915 Quantitative Methods and Analysis OR SGIA40G15 Full Stack Research Design

• None

• To furnish students with the skills to apply natural language processing methods (methods of collecting, pre-processing and analysing text data) to answer empirical questions in public policy.
• To furnish students with the skills to communicate results from text analysis to a policy audience.

• Indicative content may include:
• Use of web scraping and API to collect text data
• Methods of pre-processing text data
• Unsupervised learning methods
• Supervised learning methods
• Language models
• How to use natural language processing methods to:
• relate policy documents to the performance of policy actors
• study how policy documents are used
• investigate public sentiment towards policy actors
• analyse the changing meaning of key terms in public policy

Subject-specific Knowledge:

• Advanced knowledge of methods of collecting text data;
• Advanced knowledge of methods to pre-process text data to make it suitable for analysis;
• Advanced knowledge of natural language processing techniques, including how to appropriately use these methods to answer empirical questions in public policy, and the strengths and limitations of these methods.

Subject-specific Skills:

• Apply methods of collecting, pre-processing and analysing text data to answer an empirical question in public policy;
• The ability to effectively communicate the results of natural language processing techniques to a policy audience.

Key Skills:

• Research skills: the ability to do independent research, including the ability to design research, execute research, and critically evaluate its strengths and weaknesses.
• Communication skills: the ability to effectively communicate results from research.
• The ability to use data analysis software, including the ability to autonomously trouble-shoot using online resources.

• Teaching and learning are through a series of 1-hour lectures and computer labs.
• Lectures will familiarise students with methods of collecting, pre-processing and analysing text data, and furnish students with examples of the use of these methods in public policy.
• Computer labs will allow students to practice applying methods of collecting, pre-processing and analysing text data to the field of public policy, and to work on and receive feedback on their formative assessment.
• Summative assessment is a 3,000-word policy briefing (accounting for 100% of the final grade), which must apply natural language processing techniques to answer an empirical question in public policy.
• Formative assessment is a 750-word outline for the policy briefing, allowing students to receive feedback on their plans for the briefing.

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