Jump for page navigation or with accesskey and key 1. 
Jump to page content or with accesskey and key 2. 

Foto: Matthias Friel

Social Media & Business Analytics - Single View

Type of Course Seminar Number 436411
Hours per week in term 2 Term WiSe 2019/20
Department Wirtschaftswissenschaften   Language englisch
application period 01.10.2019 - 20.11.2019

enrollment
Gruppe 1:
     apply now / cancel application
    Day Time Frequency Duration Room Lecturer Canceled/rescheduled on Max. participants
show single terms
Seminar Di 14:00 to 18:00 wöchentlich 22.10.2019 to 04.02.2020  3.06.S12 Prof. Dr. Krasnova ,
Dr. Baumann ,
Gladkaya ,
Dr. Köster
24.12.2019: Akademische Weihnachtsferien
31.12.2019: Akademische Weihnachtsferien
Literature

Collis, J., Hussey, R. (2013). Business research: A practical guide for undergraduate and postgraduate students. Palgrave Macmillan.

Certificates

Tutorial presentation

Seminar paper

Learning Content

PLEASE NOTE THE COURSE STARTS ON TUESDAY 22.10.2019 at 14:15!
Please note that it is only possible to attend the seminar if you were present during the first session.

A number of social platforms have gained popularity in recent years (e.g. Facebook, Instagram, Airbnb, etc). Their breath-taking success manifests itself in millions of user subscriptions, significant time spent on the site, and steep growth of conducted transactions. Facebook alone has over 2.32 billion monthly active users. By rapidly changing the way we communicate, inform ourselves, spend our free time, learn and buy, these platforms transform the society we live in today. Facing this wave of new developments, many keep asking about the meaning and long-term consequences of these changes.

The main topics of the seminar will be centered around the application of various methods in the area of social media.
In general, you will work in groups consisting of two to three people.
The aim of each group is to gain expert knowledge with respect to the chosen topic (i.e., method) to be able to present it to your fellow students in the form of a tutorial session consisting of:

  • Basis concepts and theory
  • A practical example

In addition, we expect students to submit a seminar paper in the end.

Possible topics (i.e., methods) might include:

  • Eye-tracking
  • Data-scraping
  • Content analysis
  • Difference in difference
  • Structural Equation Modeling
  • ANOVA/ANCOVA
  • Grounded Theory Methodology 2.0
  • Experience sampling
  • Topic modeling
  • Multilayer Perceptrons (MLPs)
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Generative Adversarial Networks (GANs)
     

Structure Tree
Lecture not found in this Term. Lecture is in Term WiSe 2019/20 , Currentterm: SoSe 2024