Teaching

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, we will meet twice for 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.

Grading

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

Location and Date

  • Kick-Off: tbd
  • Mid-term presentations: tbd
  • Final presentation: tbd

Registration winter term 2018/19

Please register until September 30, 2018 via StudOn: https://www.studon.fau.de/crs2031328_join.html

Registration is mandatory. Places are limited. Until 30 September 2018, we will collect registrations and allocate places according to the random principle. Registration will still be possible until 12 October 2018, however you will have a higher chance of being added to the waiting list. 

 

For questions related to the seminar, please send an email to swi.seminar@gmail.com

 

Exam ID

Module number TBD Social and Web Intelligence (5 ECTS)

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