Go to JKU Homepage
Institute of Computational Perception
What's that?

Institutes, schools, other departments, and programs create their own web content and menus.

To help you better navigate the site, see here where you are at the moment.

Special Topics: Social Media Mining and Analysis

This class is usually taught by Markus Schedl in the winter term. The class is taught in English.

Information for the current semester (if available):

{{ labelInLang('cid') }} {{ labelInLang('title') }} {{ labelInLang('registration') }} {{ labelInLang('type') }} {{ labelInLang('hours') }} {{ labelInLang('teachers') }} {{ labelInLang('rhythm') }}
{{ item._id }} ({{ item.term }}) {{ item.title }}
{{ labelInLang('moreinfo') }}
{{ labelInLang('expand') }} {{ labelInLang('collapse') }}
{{ labelInLang('register') }} {{ item.type }} {{ item['hours-per-week'] }} {{ teacher.firstname }} {{ teacher.lastname }} {{ item.teachers.teacher.firstname }} {{ item.teachers.teacher.lastname }} {{ item.rhythm }}
{{ item._id }} ({{ item.term }})
{{ labelInLang('title') }} {{ item.title }}
{{ labelInLang('moreinfo') }}
{{ labelInLang('expand') }} {{ labelInLang('collapse') }}
{{ labelInLang('registration') }} {{ labelInLang('register') }}
{{ labelInLang('type') }} {{ item.type }}
{{ labelInLang('hours') }} {{ item['hours-per-week'] }}
{{ labelInLang('teachers') }} {{ teacher.firstname }} {{ teacher.lastname }} {{ item.teachers.teacher.firstname }} {{ item.teachers.teacher.lastname }}
{{ labelInLang('rhythm') }} {{ item.rhythm }}
 

Description

This course will be held foremost as an exercise in which students will implement and refine existing approaches to a task in context of social media mining or analysis. The work will be conducted in teams, each of which will select a topic to work on. The requirements to complete the course (and earn a positive grade) are the following:

  • gaining an understanding of the selected task and existing solutions
  • conducting a literature research and writing a short report about existing work on the topic (max. 3 pages)
  • implementing and evaluating a refined version of an existing approach (or an innovate novel approach)
  • giving a presentation of the topic, implemented approach/solution, and its evaluation (about 30 minutes per team)
  • writing a scientific article about the approach in the style of a conference submission (about 10 pages) 


Topics students can choose from include, but are not limited to the following (own suggestions are welcome too):

  • influential user detection
  • network structure analysis
  • sentiment analysis
  • flow analysis
  • analyzing aspects such as similarity or diversity in user preferences
  • categorization of users from their digital traces (demographics, mood, personality, habbits, etc.) 
  • studying the interrelationship between music taste and consumption patterns (e.g., time of day) or other user characteristics (e.g., country)
  • trend detection and popularity prediction
  • localizing microblog messages or other multimedia material
  • real-world event detection
  • country of origin detection (for persons, music artists, bands, or other items)

Many other possible topics can be derived, for instance, from the proceedings of the ICWSM conference:
    http://icwsm.org/2016/program/program, opens an external URL in a new window
    http://icwsm.org/2015/program/program, opens an external URL in a new window
    http://icwsm.org/2014/program/program, opens an external URL in a new window
    ...

Also the following book gives an overview about basics in mining user-generated content:
    Marie-Francine Moens, Juanzi Li, Tat-Seng Chua (eds.), Mining of User Generated Content and Its Applications, CRC Press, January 2014., opens an external URL in a new window