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DRPS : Course Catalogue : Business School : Common Courses (Management School)

Postgraduate Course: Web and Social Network Analytics (CMSE11427)

Course Outline
SchoolBusiness School CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThis course provides students both theoretical and practical fundamentals of analysing web data from various aspects, including web page analysis, social network analysis, market basket analysis, and recommendation system design.
Course description Outline Content

1. Web and web analysis evolution
2. Analysing web as a graph
3. Online social network and its analysis
4. Unsupervised techniques for analysis

Student Learning Experience

Weekly lectures and hands-on programming exercises (computer lab) in Python which enables students to implement the methodologies covered in class.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites Students MUST also take: Predictive Analytics and Modelling of Data (CMSE11428)
Prohibited Combinations Other requirements None
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Academic year 2024/25, Not available to visiting students (SS1) Quota:  None
Course Start Block 3 (Sem 2)
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 9, Seminar/Tutorial Hours 4, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 85 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) 100% coursework (individual) - assesses all course Learning Outcomes
Feedback Formative: Feedback will be provided throughout the course.

Summative: Feedback will be provided on the assessment within agreed deadlines.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Analyse a company's website and web presence
  2. Make recommendations towards improving the visibility of a company on the web
  3. Use unsupervised learning techniques for modelling customer and product recommendations
Reading List
Liu B. Web Data Mining Exploring Hyperlinks, Contents, and Usage Data / Bing Liu. Second edition. Springer; 2011.
Easley D. Networks, Crowds, and Markets: Reasoning About a Highly Connected World / David Easley, Jon Kleinberg. (Kleinberg J, ed.). Cambridge University Press; 2010.
Avinash Kaushik. Web Analytics: an Hour a Day. John Wiley & Sons; 2007.
Aggarwal CC, ed. Social Network Data Analytics. 1.. ed. Springer US: Imprint: Springer; 2011.
Kaushik A. Web Analytics 2.0: the Art of Online Accountability & Science of Customer Centricity. Wiley; 2010.
Leskovec J. Mining of Massive Datasets / Jure Leskovec, Anand Rajaraman, Jeffrey David Ullman. Third edition. (Rajaraman A, Ullman JD, eds.). Cambridge University Press; 2020.
Additional Information
Graduate Attributes and Skills Knowledge and Understanding

After completing this course, students should be able to:

Demonstrate a thorough knowledge and understanding of contemporary organisational disciplines; comprehend the role of business within the contemporary world; and critically evaluate and synthesise primary and secondary research and sources of evidence in order to make, and present, well informed and transparent organisation-related decisions, which have a positive global impact.

Identify, define and analyse theoretical and applied business and management problems, and develop approaches, informed by an understanding of appropriate quantitative and/or qualitative techniques, to explore
and solve them responsibly.

Communication, ICT, and Numeracy Skills

After completing this course, students should be able to:

Critically evaluate and present digital and other sources, research methods, data and information; discern their limitations, accuracy, validity, reliability and suitability; and apply responsibly in a wide variety of organisational contexts.

Practice: Applied Knowledge, Skills and Understanding

After completing this course, students should be able to:

Work with a variety of organisations, their stakeholders, and the communities they serve - learning from them, and aiding them to achieve responsible, sustainable and enterprising solutions to complex problems.

Cognitive Skills

After completing this course, students should be able to:

Be self-motivated; curious; show initiative; set, achieve and surpass goals; as well as demonstrating adaptability, capable of handling complexity and ambiguity, with a willingness to learn; as well as being able to demonstrate the use digital and other tools to carry out tasks effectively, productively, and with attention to
KeywordsNot entered
Course organiserDr Zexun Chen
Tel: (0131 6)50 8074
Course secretaryMs Morgan Wilson
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