COMP 3020 Social Web Analytics

Credit Points 10

Legacy Code 300958

Coordinator Gizem Intepe Opens in new window

Description The Social Web provides everyone with a voice; information from Facebook, Twitter and other social networks allows us to identify trends and relationships in society. Whilst this has interest on a personal level, the killer-apps will be in analysing social Web data for business, such as tracking the buzz around a new product, and understanding the relationships between customers and products. This unit will introduce its students to the Social Web data that is available, and blend data science and machine learning concepts to allow extraction and analysis of such data.

School Computer, Data & Math Sciences

Student Contribution Band HECS Band 1 10cp

Check your HECS Band contribution amount via the Fees page.

Level Undergraduate Level 3 subject

Pre-requisite(s) Students who are NOT enrolled in 1837 Bachelor of Cyber Security and Behaviour 3769 Bachelor of Data Science or 3770 Bachelor of Applied Data Science must have successfully completed one the following three units
Students enrolled in 1837 Bachelor of Cyber Security and Behaviour must have successfully completed the following two units
MATH 2006 Experimental Design and Analysis AND MATH 1002 Analytics Programming
MATH 1028 Statistical Decision Making OR MATH 1003 Biometry OR MATH 1030 Statistics for Business

Co-requisite(s) For students enrolled in courses 3769 Bachelor of Data Science or 3770 Bachelor of Applied Data Science
MATH 1033 Thinking About Data

Assumed Knowledge

Students are expected to be familiar with fundamental computer programming concepts.

Learning Outcomes

On successful completion of this subject, students should be able to:
  1. extract and process formatted data from social Web sources.
  2. use computer algorithms to visualise complex social Web interactions.
  3. use mathematical and statistical methods to identify significant trends in the social Web.
  4. use mathematical and statistical techniques to identify critical regions of a social network.
  5. partition a social network into clusters.
  6. choose an appropriate metric to measure the interaction between social network nodes.
  7. compute the popularity, authority and hub scores for network nodes.

Subject Content

Data extraction and formatting.
Visualisation of social networks.
Identifying trends in social networks.
Measuring similarity in multiple networks.
Clustering social network information
Finding authorities and hubs in a social network.

Assessment

The following table summarises the standard assessment tasks for this subject. Please note this is a guide only. Assessment tasks are regularly updated, where there is a difference your Learning Guide takes precedence.

Item Length Percent Threshold Individual/Group Task
Class Test 45 minutes 15 N Individual
Report - Type of Assessment Group Project Using a case study approach, groups of 4-5 students will write computer programs to extract and analyse social media data, producing a final report that will be marked. 2,000 words 25 N Group
Online quizzes (best 5 from 8 quizzes) - able to be done off campus, as a regular learning prompt. 15 minutes (per Quiz) 15 N Individual
Final Exam 2 hours 45 Y Individual

Prescribed Texts

  • Russell, M. A. (2013). Mining the social web (2nd ed.). Sebastopol, CA: O'Reilly.

Teaching Periods

2022 Trimester 1

Sydney City

Day

Subject Contact Mahsa Razavi Opens in new window

Attendance Requirements 80% attendance rate is imposed in all core subjects’ due to the nature of class activities that are aligned with subject assessments.

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2022 Trimester 2

Sydney City

Day

Subject Contact Mahsa Razavi Opens in new window

Attendance Requirements 80% attendance rate is imposed in all core subjects’ due to the nature of class activities that are aligned with subject assessments.

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2022 Semester 2

Campbelltown

Day

Subject Contact Gizem Intepe Opens in new window

Attendance Requirements 80% attendance rate is imposed in all core subjects’ due to the nature of class activities that are aligned with subject assessments.

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Penrith (Kingswood)

Day

Subject Contact Gizem Intepe Opens in new window

Attendance Requirements 80% attendance rate is imposed in all core subjects’ due to the nature of class activities that are aligned with subject assessments.

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Parramatta - Victoria Rd

Day

Subject Contact Gizem Intepe Opens in new window

Attendance Requirements 80% attendance rate is imposed in all core subjects’ due to the nature of class activities that are aligned with subject assessments.

View timetable Opens in new window