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Felicia Löcherbach is a PhD Candidate at the department of Communication Science. She is studying the diversity of issues and perspectives in (online) news and how it is affected by recommender algorithms and selective exposure. She is supervised by Wouter van Atteveldt (Vrije Universiteit Amsterdam), Damian Trilling and Judith Möller (University of Amsterdam). Her research is part of the project “Inside the filter bubble: A framework for deep semantic analysis of mobile news consumption traces” funded by a JEDS grant from NWO. 

Felicia obtained a Research Master in Communication Science at the University of Amsterdam (2018), and a Bachelor in Communication Science and Philosophy from the University of Erfurt (2016). 

Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

Field Experiment Mathematics
Recommender Systems Mathematics
Recommender systems Engineering & Materials Science
Application programs Engineering & Materials Science
Recommendations Mathematics
Logic Mathematics
Testing Mathematics
Experiments Engineering & Materials Science

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Research Output 2018 2018

  • 1 Conference contribution

3bij3: A framework for testing effects of recommender systems on news exposure

Locherbach, F. & Trilling, D., 24 Dec 2018, Proceedings - IEEE 14th International Conference on eScience, e-Science 2018. Institute of Electrical and Electronics Engineers Inc., p. 350-351 2 p. 8588712

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Field Experiment
Recommender Systems
Recommender systems
Application programs