42913 Social and Information Network Analysis
6cp; 3hpw (1.5hr seminar, 1.5hr lab, tutorial), on campus, standard.Requisite(s): (120 credit points of completed study in Bachelor's Degree owned by FEIT OR 120 credit points of completed study in Bachelor's Honours Embedded owned by FEIT OR 120 credit points of completed study in Bachelor's Combined Degree owned by FEIT OR 120 credit points of completed study in Bachelor's Combined Honours owned by FEIT OR 120 credit points of completed study in Bachelor's Combined Degree co-owned by FEIT OR 120 credit points of completed study in Bachelor's Combined Honours co-owned by FEIT) AND 31250 Introduction to Data Analytics) OR ((24 credit points of completed study in 24.0000000000 Credit Points spk(s): C04380 Master of Business Analytics OR 48 credit points of completed study in 48.0000000000 Credit Points spk(s): C04379 Master of Business Analytics (Extension)) AND (32130 Fundamentals of Data Analytics OR 36106 Machine Learning Algorithms and Applications)
These requisites may not apply to students in certain courses. See access conditions.
Postgraduate
Description
In social and economic lives, everything (e.g. people, information, business, events) is becoming more and more connected with the development of technologies such as social networks (e.g. Facebook, Twitter) and information networks (e.g. the Web). A practical way of making sense of these types of data is to analyse them as networks.
This subject introduces the students to basic concepts in social and information networks, metrics to characterise networks, models to explain the generation of networks, and methods to analyse networks. The students learn to use software tools to visualise and analyse real-world network data. The subject also introduces a wide variety of applications in social and information networks such as user recommendation and web search.
Typical availability
Autumn session, City campus
Detailed subject description.