Module Details
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.
Title COMPLEX INFORMATION NETWORKS
Code COMP324
Coordinator Dr M Zito
Computer Science
Michele@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2020-21 Level 6 FHEQ Second Semester 15

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.

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.

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)

Teaching and Learning Strategies

Teaching Method 1 - Lecture
Description:
Attendance Recorded: Yes

Teaching Method 2 - Tutorial
Description:
Attendance Recorded: Yes

Due to Covid-19, in 2020/21, one or more of the following delivery methods will be implemented based on the current local conditions.
(a) Hybrid delivery, with social distancing on Campus
Teaching Method 1 - Lecture
Description: On-line synchronous/asynchronous lectures
Teaching Method 2 - Tutorial
Description: On-line synchronous/asynchronous sessions

(b) Fully online delivery and assessment
Teaching Method 1 - Lecture
Description: On-line synchronous/asynchronous lectures
Teaching Method 2 - Tutorial
Description: On-line synchronous/asynchronous sessions

(c) Standard on-campus delivery with minimal social distancing.
As our planning has already gone too far, even if the campus opens up, we will offer hybrid teaching
Teaching Method 1 - Lecture
Description: On-li ne synchronous/asynchronous lectures
Teaching Method 2 - Tutorial
Description: Mix of on-campus/on-line synchronous/asynchronous sessions

Teaching Schedule
  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 30

   10

       40
Timetable (if known)              
Private Study 110
TOTAL HOURS 150

Assessment
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 minutes.    60       
CONTINUOUS Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
(324.3) Micro CA 3 Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 2      18       
324.2 Micro CA 2 Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 2      12       
(324.1) Micro CA 1 Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 2      10       

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