Module Specification

The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
1. Module Title Complex Information Networks
2. Module Code COMP324
3. Year Session 2023-24
4. Originating Department Computer Science
5. Faculty Fac of Science & Engineering
6. Semester Second Semester
7. CATS Level Level 6 FHEQ
8. CATS Value 15
9. Member of staff with responsibility for the module
Dr M Zito Computer Science Michele@liverpool.ac.uk
10. Module Moderator
11. Other Contributing Departments  
12. Other Staff Teaching on this Module
Mrs J Birtall School of Electrical Engineering, Electronics and Computer Science Judith.Birtall@liverpool.ac.uk
Dr U Hustadt Computer Science U.Hustadt@liverpool.ac.uk
13. Board of Studies
14. Mode of Delivery
15. Location Main Liverpool City Campus
    Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
16. Study Hours 30

  10

      40
17.

Private Study

110
18.

TOTAL HOURS

150
 
    Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other
19. Timetable (if known)            
 
20. Pre-requisites before taking this module (other modules and/or general educational/academic requirements):

COMP202 Complexity of Algorithms; COMP108 Data Structures and Algorithms; COMP116 Analytic Techniques for Computer Science
21. Modules for which this module is a pre-requisite:

 
22. Co-requisite modules:

 
23. Linked Modules:

 
24. Programme(s) (including Year of Study) to which this module is available on a mandatory basis:

25. Programme(s) (including Year of Study) to which this module is available on a required basis:

26. Programme(s) (including Year of Study) to which this module is available on an optional basis:

27. Aims
 

To understand the software development opportunities offered by the emergence of these networks, through the study of information retrieval algorithms like the one used by Google. To understand the application development possibilities offered by social networks environments like Facebook. To understand how elementary graph-theoretic concepts may help understanding the structure and certain properties (like the "mysterious" small world phenomenon, or the resilience to failures) of such networks.

 
28. Learning Outcomes
 

(LO1) At the end of this module students should be able to explain the most common metrics and techniques of complex network analysis and classification.

 

(LO2) Explain the most recent applications of these techniques in the area of social and technological networks.

 

(LO3) Be able to identify the main issues, techniques, and tools needed for the development of applications in the area of social networks.

 

(S1) Learning Skills: Design appropriate social network solutions and interface or extend the designs of existing social network infrastructures.

 

(S2) Learning Skills: Identify and analyse complex network characteristics.

 

(S3) Learning Skills: Identify and interpret domain and societal requirements for the deployment of network solutions.

 

(S4) Learning Skills: Combine knowledge from other algorithmic course to solve specific network design and analysis problems.

 

(S5) Employability Skills: Evaluate existing software systems and infrastructures

 

(S6) Employability Skills: Present a technological solution within a broader context

 

(S7) Research Skills: Establish the potential of social networking technologies in specific contexts and domains.

 

(S8) Research Skills: Articulate appropriate frameworks for the analysis of particular social networks.

 
29. Teaching and Learning Strategies
 

Teaching Method 1 - Lecture
Description:
Attendance Recorded: Yes

Teaching Method 2 - Tutorial
Description:
Attendance Recorded: Yes

Standard on-campus delivery
Teaching Method 1 - Lecture
Description: Mix of on-campus/on-line synchronous/asynchronous sessions
Teaching Method 2 - Tutorial
Description: On-campus synchronous sessions

 
30. Syllabus
   

A selection of lecture topics from the following list:

Introduction to social networks and metrics (typically 3 to 6 lectures)

Small world networks and network distance (6 lectures)

Power laws and the structure of the web (6 lectures)

Internet and robustness (6 lectures)

Community detection (6 lectures)

Network search and Google PageRank (typically 3 to 6 lectures)

Facebook and Social Network Apps (typically 6 to 9 lectures)

 
31. Recommended Texts
  Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.
 

Assessment

32. EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (324) Written Exam Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 2 150 80
33. CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (324.1) Micro CA 1 Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 2 0 10
  (324.2) Micro CA 2 Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 2 0 10