Postgraduate taught 

Data Science MSc

Web Science (M) COMPSCI5078

  • Academic Session: 2024-25
  • School: School of Computing Science
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No
  • Collaborative Online International Learning: No

Short Description

Web Science is the study of the World Wide Web (WWW), its components, facets and characteristics and the impact it has on both society and technology. The World Wide Web changed the way in which we create information, communicate and interact. New models of social networks (LinkedIn, Facebook, etc.) create opportunities, which were not available before. Exploiting such data and networks for the benefit of individuals and organizations has become a key in our knowledge society.

Timetable

TBC

Excluded Courses

None

Co-requisites

None

Assessment

Coursework 20%, Class Test 80%

(We note that there is no option for a Class Test in the list above)

Course Aims

The objective of this course is to introduce students to the field of web science and critically examine methodologies and techniques used in the field.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

 

1. Skills to analyse and implement technical solutions on social web applications

2. Describe methodologies to conduct large scale data analysis on social data and platforms

3. Describe the techniques employed in developing advertising models on the web

4. Describe the techniques needed to analyse social networks

5. Describe topic models and their usage on social systems

6. Describe sentiment and emotion extraction techniques and employ them

7. Ability to understand fairness, ethics and privacy issues on online systems

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including class tests) of the course's summative assessment.