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Description

This module is intended to provide a fundamental understanding of the contemporary concepts and techniques used for processing linguistic data in textual form (Natural Language Processing). It emphasizes the use of existing frameworks and NLP algorithms, provides students with the skills to analyse textual data, and familiarises them with tools and applications. The first part of the course introduces core topics in computational modelling (morphology) of natural language including; Regular Expressions, Finite State Transducers, Part of Speech Tagging, Stemming, and Lemmatisation. The second part of the course introduces contemporary text processing and analysis tasks such as Information Extraction, Named Entity Recognition and Sentiment Analysis, and their application to automated processing of different text sources (academic publications, social media, news articles, and humanities corpora). The module follows a combination of teaching and learning methods, including lectures and computing laboratory work by putting more emphasis on learning through practical work (exercises and mini-projects) to ground the more theoretical aspects of the module syllabus.

Learning outcomes

Upon completion of the module, students will be able to:

• Demonstrate knowledge and understanding of the fundamental concepts of Natural Language Processing and text analysis.
• Apply methods and tools in the area of computational modelling (morphology) of natural language for automatic processing of textual input.
• Explore solutions to text analysis problems in relation to automated processing tasks such as Information Extraction, Named Entity Recognition, Sentiment Analysis and other.
• Develop small scale NLP processing pipelines using existing tools and frameworks.
• Evaluate the outcome of the automated text processing pipelines according to standard metrics.

Optional for: MSc Knowledge, Information and Data Science, MA/MSc Digital Humanities, MA Archives and Records Management, MA Library and Information Studies, MA Publishing, 3rd year BSc Information Management or Business

Prerequisites: INST0019 Introduction to Programming and Scripting or equivalent experience with programming at a foundational level.

Please note: this module will be capped at 30 students.