FIBISS: Automatic Fact Checking for Biomedical Information in Social Media and Scientific Literature
January 2021 - December 2023
- Roman Klinger
- Short description
Most research on methods and models for automatic fact checking, which can distinguish misinformation and desinformation from correct information, focus on the news domain. We move to the biomedical domain and develop methods which are able to automatically verify or falsify claims like "vaccines cause autism". We link our results to reliable scientific sources automatically.
German Research Foundation (DFG)
- Long description
Most research on methods and models for automatic fact checking, which can distinguish misinformation and desinformation from correct information, focus on the news domain. News, including those shared in social media spaces, are checked for their truthfulness. Such methods have not been developed for the biomedical domain yet. Challenges include the richness of (established) sources of information, the complexity of information, as well as the differences between the language of experts and medical laypeople. In this project, we develop information extraction systems for laypeople and expert language, map the extracted information onto each other and finally check their truthfulness, based on established sources. The project combines therefore methods from transfer learning, information extraction, and fact checking for the biomedical domain, especially in social media.
- Roman Klinger
- Laura Bostan