2024W

• Experiment Design for Data Science / 188.992 / VU
• Interdisciplinary Lecture Series on Data Science / 194.046 / VU

• Improving Dropout Prediction for Informatics Bachelor Students / Kern, B. M. J. (2024). Improving Dropout Prediction for Informatics Bachelor Students. In Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 2 (pp. 830–831). https://doi.org/10.1145/3649405.3659472
• The ALPIN Sentiment Dictionary: Austrian Language Polarity in Newspapers / Kolb, T. E., Sekanina, K., Kern, B. M. J., Neidhardt, J., Wissik, T., & Baumann, A. (2022). The ALPIN Sentiment Dictionary: Austrian Language Polarity in Newspapers. In LREC 2022 Conference Proceedings (pp. 4708–4716). European Language Resources Association. https://doi.org/10.34726/4101
  Download: PDF (604 KB)
  Project: DYSEN (2020–2021)
• Evaluating Active and Assisted Living technologies: Critical methodological reflections based on a longitudinal randomized controlled trial / Bieg, T., Gerdenitsch, C., Schwaninger, I., Kern, B. M. J., & Frauenberger, C. (2022). Evaluating Active and Assisted Living technologies: Critical methodological reflections based on a longitudinal randomized controlled trial. Computers in Human Behavior, 133(107249), 107249. https://doi.org/10.1016/j.chb.2022.107249
• Creating an Austrian language polarity dictionary with the crowd / Kolb, T. E., Sekanina, K., Kern, B. M. J., Neidhardt, J., Baumann, A., & Wissik, T. (2021, December 11). Creating an Austrian language polarity dictionary with the crowd [Conference Presentation]. Workshop: “Österreichisches Treffen zu Sentimentinferenz (ÖTSI)” der Österreichischen Linguistik-Tagung 2021, Austria. http://hdl.handle.net/20.500.12708/153831
  Download: Slides of the Presentation (1.08 MB)
  Project: DYSEN (2020–2021)
• A review and cluster analysis of German polarity resources for sentiment analysis / Kern, B., Baumann, A., Kolb, T., Sekanina, K., Hofmann, K., Wissik, T., & Neidhardt, J. (2021). A review and cluster analysis of German polarity resources for sentiment analysis. In 3rd Conference on Language, Data and Knowledge (LDK 2021) (pp. 1–17). OASICS. https://doi.org/10.4230/OASIcs.LDK.2021.37
• Exploring Causal Relationships Among Emotional and Topical Trajectories in Political Text Data / Baumann, A., Hofmann, K., Kern, B., Marakasova, A., Neidhardt, J., & Wissik, T. (2021). Exploring Causal Relationships Among Emotional and Topical Trajectories in Political Text Data. In 3rd Conference on Language, Data and Knowledge (LDK 2021) (pp. 1–8). OASICS. https://doi.org/10.4230/OASIcs.LDK.2021.38