Publications

Romberg, J. (2022, October). Is Your Perspective Also My Perspective? Enriching Prediction with Subjectivity. In Proceedings of the 9th Workshop on Argument Mining (pp.115-125), Gyeongju, Republic of Korea. Association for Computational Linguistics. https://aclanthology.org/2022.argmining-1.11

Romberg, J., & Escher, T. (2022). Automated Topic Categorisation of Citizens’ Contributions: Reducing Manual Labelling Efforts Through Active Learning. In: Marijn Janssen, et al. Electronic Government. EGOV 2022. Lecture Notes in Computer Science, vol 13391. Springer, Cham. https://doi.org/10.1007/978-3-031-15086-9_24

Romberg, J., Mark, L., & Escher, T. (2022, June). A Corpus of German Citizen Contributions in Mobility Planning: Supporting Evaluation Through Multidimensional Classification. In Proceedings of the Language Resources and Evaluation Conference (pp. 2874–2883), Marseille, France. European Language Resources Association. https://aclanthology.org/2022.lrec-1.308

Romberg, J., & Conrad, S. (2021, November). Citizen Involvement in Urban Planning – How Can Municipalities Be Supported in Evaluating Public Participation Processes for Mobility Transitions?. In Proceedings of the 8th Workshop on Argument Mining (pp. 89-99), Punta Cana, Dominican Republic. Association for Computational Linguistics. https://aclanthology.org/2021.argmining-1.9

Romberg, J., Dyczmons, J., Borgmann, S. O., Sommer, J., Vomhof, M., Brunoni, C., Bruck-Ramisch, I., Enders, L., Icks, A., & Conrad, S. (2020, December). Patient Information Needs in Online Diabetes Forums. In Proceedings of the Fifth Social Media Mining for Health Applications Workshop & Shared Task (pp. 19-26), Barcelona, Spain (Online). Association for Computational Linguistics. https://aclanthology.org/2020.smm4h-1.3

Oberstrass, A., Romberg, J., Stoll, A., & Conrad, S. (2019, June). HHU at SemEval-2019 Task 6: Context does matter-tackling offensive language identification and categorization with ELMo. In Proceedings of the 13th International Workshop on Semantic Evaluation (pp. 628-634), Minneapolis, Minnesota, USA. Association for Computational Linguistics. https://www.aclweb.org/anthology/S19-2112.pdf

Cabanski, T., Romberg, J., & Conrad, S. (2017, August). HHU at SemEval-2017 Task 5: Fine-grained Sentiment Analysis on Financial Data using Machine Learning Methods. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017) (pp. 832-836), Vancouver, Canada. Association for Computational Linguistics. https://www.aclweb.org/anthology/S17-2141.pdf

Romberg, J. (2017). Comparing Relevance Feedback Techniques on German News Articles. Datenbanksysteme für Business, Technologie und Web (BTW 2017)-Workshopband. PDF