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Privacy Risks in German Patient Forums: A NER-Based Approach to Enrich Digital Twins

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Information and Software Technologies (ICIST 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1979))

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Abstract

The online sharing of personal health data by individuals has raised privacy concerns. This paper presents a Named Entity Recognition (NER)-based analysis to detect potential privacy risks in German patient forums. The objective is to extract sensitive information from user-generated texts and augment existing digital profiles of users to demonstrate the potential threats posed by the aggregation of information. To achieve this, we trained a NER model on a large corpus of German patient forum texts and evaluated its performance using standard metrics. The results show that the NER model can effectively extract health-related information from German texts with a micro-average precision of 0.8666, a recall of 0.9633 and an F1-score of 0.9124. This enables the creation of Digital Twins that accurately reflect the health-related characteristics of individuals. However, when this information is combined with data from different platforms, it poses a potential threat to users’ privacy and underlines the need to warn users.

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Notes

  1. 1.

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Acknowledgments

This research is funded by dtec.bw – Digitalization and Technology Research Center of the Bundeswehr. dtec.bw is funded by the European Union – NextGenerationEU.

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Authors and Affiliations

  1. Bielefeld University of Applied Sciences and Arts, Bielefeld, Germany

    Sergej Schultenkämper & Frederik Simon Bäumer

Authors
  1. Sergej Schultenkämper
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  2. Frederik Simon Bäumer
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Correspondence to Sergej Schultenkämper .

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Editors and Affiliations

  1. Kaunas University of Technology, Kaunas, Lithuania

    Audrius Lopata

  2. Kaunas University of Technology, Kaunas, Lithuania

    Daina Gudonienė

  3. Kaunas University of Technology, Kaunas, Lithuania

    Rita Butkienė

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Schultenkämper, S., Bäumer, F.S. (2024). Privacy Risks in German Patient Forums: A NER-Based Approach to Enrich Digital Twins. In: Lopata, A., Gudonienė, D., Butkienė, R. (eds) Information and Software Technologies. ICIST 2023. Communications in Computer and Information Science, vol 1979. Springer, Cham. https://doi.org/10.1007/978-3-031-48981-5_9

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  • DOI: https://doi.org/10.1007/978-3-031-48981-5_9

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  • Online ISBN: 978-3-031-48981-5

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