DATA419-23S1 (C) Semester One 2023

Online Communities and Social Networks

This occurrence is not offered in 2023

15 points

Details:
Start Date: Monday, 20 February 2023
End Date: Sunday, 25 June 2023
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 5 March 2023
  • Without academic penalty (including no fee refund): Sunday, 14 May 2023

Description

This course introduces to the analyses of online communities and social networks. Students will learn to formulate scientific questions about the online dynamics and use open software to collect, organize, model, and communicate data from common social networks.

We are social animals, we live in communities, we interact and shape the world together. More and more, these activities are performed online. This course introduces the mathematical, statistical and data science tools necessary to analyse scientifically the behaviour of people on Social Networks. The students will learn topics from linear algebra (matrix algebra, some spectral theory, ...), graph theory (distances, paths, ...), complex network theory (centralities, power-law distributions, homophily), statistics (exponential random models, random dot product graph models, ...), and more. The course puts a special emphasis on interdisciplinary investigation approaches. Current algorithmic implementations and robust computational frameworks will be used in the weekly laboratories.

The course syllabus is flexible, and adapts to the students' interest picking from the wide palette of tools used in social network analysis.
Guests from industry and/or academia may contribute their expertise.

Assessments are designed to encourage the student to build a data science portfolio of projects and public writing.

Learning Outcomes

  • During this course, students will learn to:
  • use statistical and mathematical notions to understand and explore complex networks;
  • formulate scientific questions about the dynamics of online social networks;
  • use open source software to collect, organize, model, and communicate data from common social networks.

Prerequisites

Subject to approval of the Head of Department of Mathematics and Statistics.

Course Coordinator

For further information see Mathematics and Statistics Head of Department

Assessment

Essay 30%
Tutorial 30%
Group Project 30%

Indicative Fees

Domestic fee $995.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see Mathematics and Statistics .

All DATA419 Occurrences

  • DATA419-23S1 (C) Semester One 2023 - Not Offered
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