Social and Web Intelligence Seminar


Content and goals of the course

Social media became an inseparable part of today’s companies. The vast amount of user generated data online gives huge advantages to companies primarily by providing them with easy access to customer data free of charge. With every action online, users leave a trace behind which companies can use for a wide variety of decisions – product development and improvement, more targeted advertising, customer support. The user data come in various forms: text, images, videos.

In this seminar we put special focus on text and network data. We first teach the theory behind text and network mining and then apply this knowledge in to given datasets. This is the practical part which will be done during the semester.

For the Master IIS students, the seminar can be chosen as part of the „Business Analytics“ specialization, as well as an elective in the module IIS Management Electives – Services, Processes, Intelligence II.

Prerequisite: Students should have successfully passed the E-Business Intelligence and Relationships lecture at our Chair before taking this course. A similar introductory course in data analysis may also be considered.

Course structure

The course consists of four main parts:

  1. Introduction
  2. Social Network Mining
  3. Text Mining
  4. Applications

Please note: The lecture videos are pre-recorded and will be available online via StudOn. Students can watch the lectures online at their own convenience. Even though there is no exam on the lecture material, it is necessary to watch the lectures in order to work on the mid-term exercises and the final exercise task.

During the semester you will work on two mid-term presentations. One will be an exercise on network analysis, and the other on text mining. For each of the exercises, we will give datasets and the tools you’ll be working with. Work will be done in groups. The idea behind this, is for you to work on the topics during the semester, after you have familiarized yourselves with each theoretical part, and can apply the knowledge on a dataset. These two presentations won’t be graded.

The final exercise will give you the chance to apply both types of analysis, network and text analysis, on the same dataset. For this final task, you will have to make a presentation and write a paper.

The exam will be in the form of a presentation and seminar paper on a given topic and dataset.


  • Final presentation: 30%
  • Seminar paper: 70%

Location and Date

  • Kick-Off: 25.10.2019 at 11 am in room 0.423
  • Mid-term presentations: online
  • Final presentation: online

Please note: The seminar will be done entirely online. There will be no lectures or presentations that require presence except attending 2 kick-off appointments: the first one is on 25.10.2019 when you will get more information on the course as well as form groups. The second kick-off will be in December and we will then provide more information on the final exercise. You will upload the mid-term and final presentations online and will get feedback from us via email.

Registration winter term 2019/20

Registration is open between September 09 and October 18, 2019 via StudOn: https://www.studon.fau.de/crs2678829_join.html 

Registration is mandatory. Places are limited to 25. Until October 18 2019, we will collect registrations and allocate places according to the first come first served principle. Please note that registration will be possible until 18 October 2019, however this does not guarantee that you will be offered a place.  


For questions related to the seminar, please send an email to pavlina.kroeckel@fau.de


Exam ID

Module number Social and Web Intelligence  3300 (5 ECTS)

Exam number Social and Web Intelligence (portfolio) 33004 (5 ECTS)