851-0585-45L  Machine Learning and Modelling for Social Networks

SemesterFrühjahrssemester 2017
DozierendeO. Woolley, N. Antulov-Fantulin, I. Moise, L. Sanders
Periodizitätjährlich wiederkehrende Veranstaltung
LehrspracheEnglisch
KommentarNumber of participants limited to 50.



Lehrveranstaltungen

NummerTitelUmfangDozierende
851-0585-45 VMachine Learning and Modelling for Social Networks
Dates: 8.5. - 12.5.2017, 9-12
15s Std.
08.05.09:15-12:00HG E 3 »
09.05.09:15-12:00ML H 37.1 »
10.05.09:15-12:00ML H 37.1 »
11.05.09:15-12:00LEE E 101 »
12.05.09:15-12:00LEE E 101 »
O. Woolley, N. Antulov-Fantulin, I. Moise, L. Sanders

Katalogdaten

KurzbeschreibungThis mini-course covers computational and statistical methods to characterize the structure and dynamics of complex social networks. We cover methods such as clustering, classification, spectral analysis and Montecarlo and also specific applications to social network data and spreading processes on these networks. We discuss current research and ethical questions raised by applications.
LernzielThis advanced course will give students insight into the questions that can be answered analyzing network data and into the related challenges. They will be exposed to the main methods that can be used to tackle these questions and learn about the shortcomings of these current methods. We will also raise students awareness of some of the ethical questions raised, mainly in the realm of privacy, by the types of data collected and the influence on individual behavior that can be achieved through technologies built on the methods presented in class. Students will be encouraged to apply their knowledge to a specific network dataset by producing a research proposal.
Voraussetzungen / BesonderesStudents must be in their 5th semester or more advanced.
Knowledge of basic: linear algebra, differential equations, probability, statistics and programming.

Leistungskontrolle

Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)
Leistungskontrolle als Semesterkurs
ECTS Kreditpunkte2 KP
PrüfendeO. Woolley, N. Antulov-Fantulin, I. Moise, L. Sanders
Formbenotete Semesterleistung
PrüfungsspracheEnglisch
RepetitionRepetition ohne erneute Belegung der Lerneinheit möglich.
ZulassungsbedingungStudents must be in their 5th semester or more advanced.
Knowledge of basic: linear algebra, differential equations, probability, statistics and programming.
Zusatzinformation zum PrüfungsmodusGrades will be based on contribution to discussion and on a research proposal applying the tools and/or addressing questions discussed in the course.

Lernmaterialien

Keine öffentlichen Lernmaterialien verfügbar.
Es werden nur die öffentlichen Lernmaterialien aufgeführt.

Gruppen

Keine Informationen zu Gruppen vorhanden.

Einschränkungen

PlätzeMaximal 50
WartelisteBis 12.02.2017

Angeboten in

StudiengangBereichTyp
GESS Wissenschaft im Kontext (Science in Perspective)SoziologieWInformation