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HE Unit Template
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Social Media Intelligence
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AIWSU7025 - Social Media Intelligence
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20250200
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Course
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Unit
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1.1
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2026-09-10
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2026-09-10
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Information Technology
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Institute of Innovation, Science & Sustainability
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Information Technology
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Postgraduate - Coursework
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15
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.125
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029999
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Information Technology, n.e.c.
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029999 - Information Technology, n.e.c.
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<a href="http://www.federation.edu.au/locate/unit/aiwsu7025">View unit fees</a>
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Graded (e.g. HD, D, C, etc)
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Masters Degree
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Intermediate
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<p>Social Media Intelligence presents the theory and practice of extracting and analysing information from social media networks. The aims are to identify properties of social networks, and to make predictions about future events. Topics included will cover areas such as Graph theory, Game theory and Network dynamics and we will identify how these can be used to model and extract information from Facebook and Twitter.</p>
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<p>• Graphs</p>
<p>• Strong and weak ties</p>
<p>• Networks in their surrounding contexts</p>
<p>• Positive and negative relationships</p>
<p>• Games</p>
<p>• The structure of the web</p>
<p>• Link Analysis and web search</p>
<p>• Information Cascades</p>
<p>• Power Laws and Rich-get-richer phenomenon</p>
<p>• Cascading Behaviour in Networks</p>
<p>• The small world phenomenon</p>
<p>• Voting</p>
<p><br></p>
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<p>Where supplementary assessment is available a student must have failed overall in the Unit but gained a final mark of 45 per cent or above, has completed all major assessment tasks (including all sub-components where a task has multiple parts) as specified in the Unit Description and is not eligible for any other form of supplementary assessment.</p>
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Semester
Semester
0200
Year
Year
2027
Current Year
2026
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AIWSU7025 - Social Media Intelligence
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AIWSU7025 - Social Media Intelligence
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Unit
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Semester
Semester 1
Semester 2
Summer Semester
Year
2027
2026
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Overview
Key information
Requisites
Learning outcomes
Assessment
Parent Region
Overview
Unit description
<p>Social Media Intelligence presents the theory and practice of extracting and analysing information from social media networks. The aims are to identify properties of social networks, and to make predictions about future events. Topics included will cover areas such as Graph theory, Game theory and Network dynamics and we will identify how these can be used to model and extract information from Facebook and Twitter.</p>
Unit content
<p>• Graphs</p> <p>• Strong and weak ties</p> <p>• Networks in their surrounding contexts</p> <p>• Positive and negative relationships</p> <p>• Games</p> <p>• The structure of the web</p> <p>• Link Analysis and web search</p> <p>• Information Cascades</p> <p>• Power Laws and Rich-get-richer phenomenon</p> <p>• Cascading Behaviour in Networks</p> <p>• The small world phenomenon</p> <p>• Voting</p> <p><br></p>
Key information
Institute / school:
Institute of Innovation, Science & Sustainability
Discipline:
Information Technology
Study level:
Postgraduate - Coursework
Credit points:
15
EFTSL:
0.125
Field of education:
029999 - Information Technology, n.e.c.
Grade scheme:
Graded (e.g. HD, D, C, etc)
Placement component:
No
Fee information:
<a href="http://www.federation.edu.au/locate/unit/aiwsu7025">View unit fees</a>
Requisites
Prerequisite
None
Corequisite
None
Exclusion
None
Learning outcomes
Learning outcomes
<p>On successful completion of this unit, students are expected to gain the following [K]nowledge, [S]kills and [A]pplication of knowledge & skills</p>
Learning Outcomes
Ref
Outcome
K1
<p>Identify and describe properties of social media networks. </p>
S1
<p>Compute graph statistics from given social media networks</p>
S2
<p>Analyse simple games and describe their connection to social media networks</p>
S3
<p>Compute and interpret centrality scores over social media networks</p>
S4
<p>Generate and identify small world networks</p>
Assessment
Learning Tasks and Assessment
Ref
Learning task
Assessment type
Weighting
Learning outcomes assessed
1
<p>5 x 30-minute quizzes</p>
<p>Quiz</p>
<p>20%</p>
K1, S1, S2, S3, S4
2
<p>2000-word report</p>
<p>Report</p>
<p>30%</p>
S1
3
<p>2 hour final exam</p>
<p>Final Exam</p>
<p>40%</p>
K1, S1, S2, S3, S4
Supplementary assessment available:
Yes
Supplementary assessment information:
<p>Where supplementary assessment is available a student must have failed overall in the Unit but gained a final mark of 45 per cent or above, has completed all major assessment tasks (including all sub-components where a task has multiple parts) as specified in the Unit Description and is not eligible for any other form of supplementary assessment.</p>
Key information
Institute / school:
Institute of Innovation, Science & Sustainability
Discipline:
Information Technology
Study level:
Postgraduate - Coursework
Credit points:
15
EFTSL:
0.125
Field of education:
029999 - Information Technology, n.e.c.
Grade scheme:
Graded (e.g. HD, D, C, etc)
Placement component:
No
Fee information:
<a href="http://www.federation.edu.au/locate/unit/aiwsu7025">View unit fees</a>
Additional information
Add Info Static Text
Internal reference: AIWSU7025 - U1.1