Publikationen
Diese Webseite enthält nur Publikationen, die im Rahmen dieser Gruppe entstanden sind. Für eine detaillierte Literaturliste der einzelnen Mitglieder siehe hier oder dort.
Buchbeiträge
| 2025 | J. Dörpinghaus, V. Weil, M. Sommer, M. Tiemann and K. Hein. Modeling and analysis of longitudinal labor market social networks. Recent Advances in Computational Optimization Results of the Workshops on Computational Optimization and Numerical Search and Optimization. Stefka Fidanova (Ed.). in press: Springer, 2025. |
| M. Tiemann, J. Dörpinghaus: Computational Social Sciences. Handbuch Methoden der empirischen Sozialforschung. Nina Baur, Jörg Blasius (Eds.). To appear: Springer, 2025. | |
| J. Binnewitt, M. Tiemann, J. Dörpinghaus: Text Mining. Handbuch Methoden der empirischen Sozialforschung. Nina Baur, Jörg Blasius (Eds.). To appear: Springer, 2025. | |
| J. Dörpinghaus, M. Tiemann (Eds.). Advances in Computational Social Sciences. In preparation with Springer. | |
| 2024 |  J. Dörpinghaus, M. Tiemann. Künstliche Intelligenz – aktueller Treiber der Transformation? Datenreport zum Berufsbildungsbericht 2024. Bundesinstitut für Berufsbildung (Hrsg.), 2023, pp. 386-388. |
| J. Dörpinghaus, V.Weil, J. Binnewitt. Towards the analysis of longitudinal Data in Knowledge Graphs on Job Ads. Recent Advances in Computational Optimization Results of the Workshops on Computational Optimization and Numerical Search and Optimization. Stefka Fidanova (Ed.). Springer, 2024. |
Publikationen mit Peer-Review
| 2025 | M. Merkel, J. Dörpinghaus. The Transformative Potential of AI in Software Engineering: A case study on LeetCode and ChatGPT. Submitted. |
| M. Merkel, J. Dörpinghaus. AI in German Computer Science VET Programs: A Pilot Study on Software Development. Submitted. | |
| J. Dörpinghaus, V. Weil, R. Rockenfeller, M. P. Mangroliya. A novel approach towards the robustness of centrality measures in networks. Social Sciences & Humanities Open, 11 (2025). |
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| 2024 | T. Reiser, J. Dörpinghaus, P. Steiner, M. Tiemann. Towards a datatset of digitalized historical German VET and CVET regulations. Data, 9(11):128 (2024). |
| J. Dörpinghaus. Complex network analysis of biblical texts: A case study on Acts. Submitted. | |
| J. Dörpinghaus, V. Weil, M. W. Sommer. Modeling and analysis of longitudinal social networks. Applied Network Science, 9, 52 (2024) |
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| T. Asselborn, J. Dörpinghaus, F. Kausar, R. Möller, S. Melzer: Enhancing Text Recognition of Damaged Documents through Synergistic OCR and Large Language Models. Accepted at FedCSIS 2024. | |
| M. P. Mangroliya, J. Dörpinghaus, R. Rockenfeller. Towards the analysis of errors in centrality measures in perpetuated networks. Proceedings of the 19th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 39, pages 417–428 (2024) |
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| R. Fechner, J. Dörpinghaus. No Train, No Pain? Assessing the Ability of LLMs for Text Classification with no Finetuning. Accepted at FedCSIS 2024. | |
| M. Tiemann, J. Dörpinghaus, V. H. Shivashankar. An analysis of Computer Science in OJAs with a dual-lingual ontology approach. INFORMATIK 2024, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik, p. 2041-2052. |
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| D. Martić, A. Fischer, J. Dörpinghaus. Extending the German Labor Market Ontology with Online Data. INFORMATIK 2024, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik, p. 2013-2024. |
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| M. P. Mangroliya, J. Dörpinghaus, R. Rockenfeller. Node and Edge Removal on Complex Networks in Labor Market Research and their Influence on Centrality Measures. INFORMATIK 2024, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik, p. 2029-2040. |
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| R. Fechner, J. Dörpinghaus, R. Rockenfeller, J. Faber. Ensemble of HMMs for Sequence Prediction on Multivariate Biomedical Data. BioMedInformatics 2024, 4(3), 1672-1691 |
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| T. Reiser, J. Dörpinghaus, P. Steiner. Analyzing Historical Legal Textcorpora: German VET and CVET regulations. INFORMATIK 2024, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik, p. 2001-2012. |
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| J. Dörpinghaus, J. Binnewitt, D. Samray, K. Hein. Understanding Informatics in Continuing Vocational Education and Training Data in Germany. ACM Transactions on Computing Education, 2024, 24(3), 1-22. |
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| The Social Network of Philip in Acts: A dynamic pioneering missionary. Biblical Theology Bulletin 2024, 54(1), 50-73. |
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| A. Fischer, J. Dörpinghaus. Web Mining of Online Resources for German Labor Market Research and Education: Finding the Ground Truth? Knowledge 2024, 4(1), 51–6 |
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| J. Dörpinghaus. Automated Annotation of Parallel Bible Corpora with Cross-Lingual Semantic Concordance. Natural Language Engineering, 2024. |
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| 2023 | J. Dörpinghaus, D. Samray, R. Helmrich. Challenges of Automated Identification of Access to Education and Training in Germany. Information 2023, 14(10), 524 |
| J. Dörpinghaus, J. Binnewitt, S. Winnige, K. Hein, K. Krüger. Towards a German Labor Market Ontology: Challenges and Applications. Applied Ontology, vol. 18, no. 4, pp. 343-365, 2023. |
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| J. Dörpinghaus. Digital and Network-Based Methods for Narrative Criticism. Svensk Exegetisk Årsbok, 88(1) pp. 106–134. |
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| J. Dörpinghaus, V. Weil, M. W. Sommer. Towards modelling and analysis of longitudinal social networks. Communication Papers of the 18th Conference on Computer Science and Intelligence Systems, 2023, pp. 81–89. |
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| F. Derksen, J. Dörpinghaus. Digitalization and Sustainability in German Continuing Education. INFORMATIK 2023, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik, p. 1945-1954. |
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| R. Fechner, J. Dörpinghaus, A. Firll. Classifying Industrial Sectors from German Textual Data with a Domain Adapted Transformer. Proceedings of the 18th Conference on Computer Science and Intelligence Systems, 2023, pp. 463–470. |
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| 2022 | J. Dörpinghaus. Social Network Analysis and Co-Occurrence: Identifying the Gaps. Proceedings of the Workshop on Humanities-Centred Artificial Intelligence co-located with 45th German Conference on Artificial Intelligence, 2022. |
| J. Dörpinghaus, V. Weil, J. Binnewitt. Analyzing longitudinal Data in Knowledge Graphs utilizing shrinking pseudo-triangles. Proceedings of the of the 17th Conference on Computer Science and Intelligence Systems, 2022. |
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| J. Dörpinghaus, V. Weil, C. Düing, M. Sommer. Centrality Measures in multi-layer Knowledge Graphs. Communication Papers of the of the 17th Conference on Computer Science and Intelligence Systems pp. 163–170, 2022. |
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| J. Dörpinghaus, T. Hübenthal, J. Faber. A novel link prediction approach on clinical knowledge graphs utilising graph structures. Proceedings of the of the 17th Conference on Computer Science and Intelligence Systems pp. 43–52, 2022. |
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| J. Dörpinghaus. Wissensgraphen: Interdisziplinäre Perspektiven für Linked Data in den Geisteswissenschaften. Zeitschrift für digitale Geisteswissenschaften (ZfdG), Heft 7.2022. |
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| J. Dörpinghaus, C. Düing, S. Klante, M. Christian. From Social Networks to Knowledge Graphs: A plea for interdisciplinary approaches. Social Sciences & Humanities Open, 6(1). |
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| J. Dörpinghaus, A. Stefan, B. Schultz, M. Jacobs. Context Mining and Graph Queries on Giant Biomedical Knowledge Graphs. Knowledge and Information Systems (KAIS), 2022(64). |
Poster und Konferenzbeiträge mit Peer-Review
| 2024 | S. Udelhofen, J. Dörpinghaus. 2024. IT Professionals in Germany. Labor Market Demands of Computer Science Education and their Perception on Social Media. In Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 2 (ITiCSE 2024). Association for Computing Machinery, New York, NY, USA, 802. |
| K. Kostadinovska, J. Dörpinghaus. Educational pathways in a German labor market knowledge graph. Poster, acceptet at DAI-EaR’24 at Informatik 2024. |
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| S. Udelhofen, J. Dörpinghaus, M. Tiemann: Transforming VET research through data science? Opportunities, challenges, restrictions and connections. Workshop, Nordyrk conference 2024, Reykjavík, Iceland. |
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| K. Hein, J. Dörpinghaus: What is said about VET on social media in Germany? Trends, demands, and opinions. Nordyrk conference 2024, Reykjavík, Iceland. |
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| A. Firl, J. Dörpinghaus, R. Helmrich, M. Tiemann: Evolving trends and digitization for vocational education in Germany on YouTube. Nordyrk conference 2024, Reykjavík, Iceland. |
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| T. Reiser, J. Dörpinghaus, P. Steiner: Learning from historical VET and CVET regulations in Germany: What should VET look like and whom should it serve? Nordyrk conference 2024, Reykjavík, Iceland. |
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| J. Dörpinghaus, R. Helmrich: German CVET advertisement: Do we see a connection between Digitalization and Sustainability? Poster, 13th Researching Work & Learning (RWL), Linköping, Sweden. |
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| M. Tiemann, S. Udelhofen, J. Dörpinghaus, D. Peachkah, A. Vahdatnia: Twitter data in substantial VET research: Discussing occupations, briefly but thoroughly. 13th Researching Work & Learning (RWL), Linköping, Sweden. |
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| M. Tiemann, R. Helmrich, J. Dörpinghaus: Surveys and Big Data: Closing the gap? 13th Researching Work & Learning (RWL), Linköping, Sweden. |
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| J. Dörpinghaus, R. Helmrich, M. Tiemann. Towards an analysis of perception biases in historical networks: Synergies between Social Sciences and Digital Humanities. Poster, Digital Humanities Conference 2024, Washington DC, USA. | |
| S. Udelhofen, J. Dörpinghaus, M. Tiemann, T. Reiser, P. Steiner: Reinventing Historical Sources as New Computational Social Science Data: Regulations for Vocational Education over Time in Germany. Digital Humanities Conference 2024, Washington DC, USA. | |
| M. Tiemann, J. Dörpinghaus: Where is the AI? A case study on VET and CVET advertisements. IX Stockholm International Conference & Research Workshop on VET. |
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| J. Dörpinghaus, M. Tiemann: How does social media data reflect labour market demands: A case study on vocational education and continuing education in Germany. IX Stockholm International Conference & Research Workshop on VET. |
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| 2023 | M. Tiemann, J. Dörpinghaus. Vocational Education and Training Data in Twitter: Making German Twitter Data Interoperable. Poster, ASIS&T Annual Meeting 2023. |
| J. Dörpinghaus. Algorithmic challenges towards temporal data in social network analysis. Accepted at GrapHNR 2023: Graphs and Networks in the fourth dimension – time and temporality as categories of connectedness. | |
| J. Dörpinghaus, J. Binnewitt, K. Hein. Evaluating Computer Science Education: Lessons from Continuing Vocational Training Course. 2023 Conference on Innovation and Technology in Computer Science Education. |
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| 2022 | J. Dörpinghaus, J. Binnewitt, S. Winnige. Generating Linked Skills Data for Knowledge Discovery in German Labor Market Documents. Knowledge, skills, behaviours: An international workshop. Brighton, 2022. |
Weitere Konferenzbeiträge
| 2024 | M. Tiemann, S. Udelhoven, J. Dörpinghaus, R. Helmrich. Berufsbildungsforschung in Social Media: Perspektiven nach 2023? Poster, Nachhaltige Archivierung, Erschließung, Bereitstellung dynamischer Daten aus sozialen Medien – Twitter und danach, 2024. |
| 2023 | T. Reiser, J. Dörpinghaus. Die Verwendung der GLMO zur Verknüpfung von großen Textkorpora aus Berufsbildungsforschung und Stellenanzeigen. Poster, 6. OJA Forum, 2023. |
Preprints
| 2024 | J. Dörpinghaus, D. Stepanov, T. Hübenthal. A novel DFS/BFS approach towards link prediction. 2024. Preprint at https://arxiv.org/abs/2409.11687 |
| 2023 | J. Dörpinghaus, D. Samray, R. Helmrich. Rule-based detection of access to education and training in Germany. Accepted at the International Conference on Computational Science (ICCS), 2023. Preprint at arXiv:2304.06307. |
| J. Dörpinghaus, D. Samray, R. Helmrich. Rule-based detection of access to education and training in Germany. Accepted at the International Conference on Computational Science (ICCS), 2023. Preprint at arXiv:2304.06307. | |
| 2022 | J. Dörpinghaus, V. Weil, C. Düing, M. W. Sommer. Centrality Measures in multi-layer Knowledge Graphs. Preprint at arXiv:2203.09219. |