@inproceedings{, author = {Schultenkämper, Sergej; Bäumer, Frederik Simon; Bellgrau, Benjamin; Lee, Yeong Su; Geierhos, Michaela}, title = {From Digital Tracks to Digital Twins : On the Path to Cross-Platform Profile Linking}, editor = {Sales, Tiago Prince; Kinderen, Sybren de; Proper, Henderik A.; Pufahl, Luise; Karastoyanova, Dimka; van Sinderen, Marten}, booktitle = {Enterprise Design, Operations, and Computing. EDOC 2023 Workshops : IDAMS, iRESEARCH, MIDas4CS, SoEA4EE, EDOC Forum, Demonstrations Track and Doctoral Consortium, Groningen, The Netherlands, October 30–November 3, 2023, Revised Selected Papers}, series = {Lecture Notes in Business Information Processing}, journal = {}, address = {Cham}, publisher = {Springer}, edition = {}, year = {2024}, isbn = {978-3-031-54711-9 ; 978-3-031-54712-6}, volume = {498}, number = {}, pages = {158–171}, url = {https://doi.org/10.1007/978-3-031-54712-6_10}, doi = {10.1007/978-3-031-54712-6_10}, keywords = {Profile Matching ; Identity Linkage ; Social Media}, abstract = {In recent years, many studies have focused on correlating the profiles of real users across different social media. On the one hand, this provides a better overview of the user’s social behavior; on the other hand, it can be used to warn of possible abuse through identity theft or cyberbullying. We try to make the threat on the Web predictable for the individual user by creating digital twins. To do this, it is important to use different data sources and to merge overlapping data across platforms. In this paper, we show that YouTube is a suitable entry point into the online social network for making connections between platforms, tracking user activity across platforms, and finally merging the collected profile information into an overall picture, the digital twin.}, note = {}, institution = {Universität der Bundeswehr München, Fakultät für Informatik, INF 7 - Institut für Datensicherheit, Professur: Geierhos, Michaela}, }