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Prof. Dr. S. Decker
RWTH Aachen
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Dynamic influence network models and weak signals in social media

Thesis type
  • Diplom
Student Jan-Martin Pulwitt
Status Finished
Submitted in 2011
Proposal on 20. Jul 2010 17:30
Proposal room Seminarraum I5
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Presentation on 15. Mar 2011 16:45
Presentation room Seminarraum I5
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The available amount of available media becomes massive: in contrast to several news sources each individual can become a source of information. Processing of all the available information by single humans is impossible, even automated computation is challanging. Consequently intelligent content selection gains relevancy. On the other hand social media provide insights not possible before, trends are visible at their origins and can objectively be quantified and analyzed. This builds up the potential to combine the tasks of content selection and trend detection in an integrated approach: Weak-signal detection using influence network models.

You task will be to create and evaluate a framework capable to identify weak signals in social media, as a mean to identify strong trends before directly observable paramters suggest so. Formal influence models serve as a theoretic foundation to model the complex underlying information diffusion processes.


The applicant should be open for interdisciplinary work. She/he should be experienced in databases(IBM DB2), XML and Java or the other object-oriented programming language, simulation frameworks and has a good mathematic background. The applicant should also be a good team player to cooperate with colleagues. The knowledge of English language is a benefit

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