IB9CW-15 Text Analytics
Introductory description
This module will introduce students to the exciting area of Text Analytics. The topics covered include (but are not limited to): Sentiment Analysis, Opinion Mining, Topic Modeling and Latent Dirichlet Allocation.
Module aims
Familiarity with certain software tools to perform data mining and text mining and produce appropriate reports.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
Information retrieval and classification.
Text preprocessing and information extraction.
Sentiment Analysis.
Topic modelling.
Communicating results.
Learning outcomes
By the end of the module, students should be able to:
- Demonstrate in depth knowledge of text analytics, preparation of executive reports, and practical applications.
- Given a business problem involving text analytics, to be able to choose appropriate techniques.
Indicative reading list
Modern Information Retrieval: The Concepts and Technology behind Search (ACM Press Books) 2010 by Dr Ricardo BaezaYates, Dr Berthier Ribeiro-Neto.
Subject specific skills
Process and prepare textual data for analysis.
Use textual data to improve predictive models.
Build and understand predictive models.
Compare and explain complex models.
Transferable skills
Be able to work within a team to analyse text data issues and propose solutions.
Be able to anticipate practical implications of working with different text mining techniques.
Study time
| Type | Required |
|---|---|
| Other activity | 27 hours (18%) |
| Private study | 49 hours (33%) |
| Assessment | 74 hours (49%) |
| Total | 150 hours |
Private study description
Self study to include preparation for assessment and pre-reading for lectures and exercises
Other activity description
This module will be split as 2/3rds workshops and 1/3rd online lecture hours. The lecture hour may be live, or may be prerecorded, or asynchronous tasks with either online or face-to-face support. The module may run across one or two weeks.
Costs
No further costs have been identified for this module.
You do not need to pass all assessment components to pass the module.
Assessment group A2
| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
Assessment component |
|||
| Individual Assignment | 60% | 44 hours | Yes (extension) |
Reassessment component is the same |
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Assessment component |
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| Group Report | 40% | 30 hours | No |
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1500 words |
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Reassessment component is the same |
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Feedback on assessment
Assessments are graded using standard University Postgraduate Marking Criteria and written feedback is provided. Feedback for individual essays includes comments on a marksheet.
Courses
This module is Optional for:
- Year 1 of TIBS-N1N3 Postgraduate Taught Business Analytics