Teaching

Social and Web Intelligence Seminar

Information about the seminar for WS 2020-21

Dear students,

The seminar will take place in the upcoming WS and will be entirely online

Registration is not yet possible. See below.

Important note: In order to attend the seminar, students should have successfully taken our Business Intelligence course or a similar introductory lecture in data mining and business intelligence/machine learning. Students are expected to be familiar with the basic data mining steps and the most used algorithms (ANNs, decision trees, clustering algorithms etc.).

In case of questions, send me an email.

Pavlina Kröckel

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 on to given datasets.

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 Business Intelligence 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.

The core parts of the seminar are social networks and text mining. After the theory of each part is introduced, you will work on small exercises and answer open questions. This is part of the mid-term grading which accounts for 50% of the final grade. This will be done during the semester as individual work.

For the final task, you will be given a dataset and you will have to apply the knowledge from both social networks and text mining to solve the case. Work will be done in groups. You will have to submit a narrated presentation with your results and details in the notes section. This will account for 50% of your final grade.

Grading

  • Mid-term tasks and/or open questions: 50% (individual work)
  • Final project – narrated presentation: 50% (group work)

Location and Date

  • Kick-Off: 04.11.2020 at 10 AM via Zoom (Link on StudOn)
  • Lecture and exercise materials will be uploaded on StudOn

Please note: The seminar will be done entirely online. There will be no lectures or presentations that require presence.

Registration winter term 2020/21

Registration will open end of September/beginning of October 2020 via StudOn: https://www.studon.fau.de/crs3202793_join.html

Deadline to register is October 23, 2020.

Registration is mandatory. Places are limited to 25. Until October 23 2020, we will collect registrations and allocate places according to the first come first served principle. Please note that registration will be possible until 23 October 2020, 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)