42913 Social and Information Network Analysis6cp; 3hpw (1.5hr seminar, 1.5hr lab, tutorial), on campus, standard. Forms of attendance, mode of delivery and assessment requirements in this subject have changed to enable social distancing and reduce the risks of spreading COVID-19 in our community. Consequently, the Subject Outline information for this subject has changed. Details of the changes are published in an addendum to the Subject Outline which is available on UTSOnline/Canvas.
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 31005 Machine Learning) OR 32513 Advanced Data Analytics Algorithms )
These requisites may not apply to students in certain courses. See access conditions.
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.
Autumn session, City campus
Detailed subject description.