Statistical analysis in modern academia - Einzelansicht

The academic world increasingly faces challenges related to publication misconduct. Many ethically questionable practices are related to predatory jour- nals and predatory publishers, as these do not implement
and enforce sound quality control measures. A list of these ”bad players”, known as Beall’s List [Bea], can help researchers to avoid publishing in outlets of questionable quality. The list is not free from criticism,
though, and it is curated by humans. This list may also not be complete. This project aims to use statistics and machine learning techniques to automatically separate the good from the bad journals. The
objective of this project are to devise and implement algorithms that will identify and separate ”good” and ”bad” academic journals.

Time and place will be announced at the project fair.

B.Sc. Medieninformatik / Informatik

M.Sc. Computer Science and Media / Computer Science for Digital Media

M.Sc. Human-Computer Interaction

M.Sc. Digital Engineering