Social Media Research Project - Einzelansicht

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

Tutorial presentation

Seminar paper

Blog article

PLEASE NOTE THE COURSE STARTS ON TUESDAY 22.10.2019 at 14:15 in the room 3.06.S12!

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. Furthermore, students will be expected to write down a blog article (nice example for a blog article): http://ruder.io/optimizing-gradient-descent/index.html).

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)