About our project:
E-data & research: LISS panel ingezet voor online communicatie-onderzoek, door Liesje van der Linden
NEMO Kennislink: AI tilt discussie naar hoger niveau, door Mathilde Jansen
Publications from our project:
- Waterschoot, C., van den Hemel, E., & van den Bosch, A. (2024, September). The Impact of Featuring Comments in Online Discussions. In International Conference on Advances in Social Networks Analysis and Mining (pp. 65-74). Cham: Springer Nature Switzerland.
- Waterschoot, C. D. K. (2024). The Constructive Conundrum: Computational Approaches to Facilitate Constructive Commenting on Online News Platforms (Doctoral dissertation, Utrecht University).
- Van der Linden, L., Waterschoot, C., van den Hemel, E., Kunneman, F., Bosch, A. v. d., & Krahmer, E. (2024, June 18). Who Are the Online Commenters: A Large-scale Representative Survey to Explore the Identity and Motivation of Online Commenters. PsyArXiv preprint.
- Waterschoot, C., & van den Bosch, A. (2024). A time-robust group recommender for featured comments on news platforms. Frontiers in big Data, 7, 1399739.
- Waterschoot, C., & Bosch, A. V. D. (2023). Hybrid moderation in the newsroom: Recommending featured posts to content moderators. arXiv preprint arXiv:2307.07317.
- Waterschoot, C., van den Hemel, E., & van den Bosch, A. (2022, October). Detecting minority arguments for mutual understanding: A moderation tool for the online climate change debate. In Proceedings of the 29th International Conference on Computational Linguistics (pp. 6715-6725).
- Waterschoot, C., van den Hemel, E., & van den Bosch, A. (2022). Detecting Minority Arguments for Mutual Understanding: A Moderation Tool for the Online Climate Change Debate. In Proceedings of the 29th International Conference on Computational Linguistics, (pp. 6715–6725), Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
- Waterschoot, C., van den Bosch, A., & van den Hemel, E. (2021). Calculating Argument Diversity in Online Threads. In 3rd Conference on Language, Data and Knowledge (LDK 2021) (pp. 39-1). Schloss Dagstuhl–Leibniz-Zentrum für Informatik.
Conference presentations:
Relevant publications from previous projects:
- Kunneman, F., Wubben, S., van den Bosch, A., & Krahmer, E. (2018, November). Aspect-based summarization of pros and cons in unstructured product reviews. In COLING (pp. 2219-2229).
- Kunneman, F., Ferreira, T. C., Krahmer, E., & Van Den Bosch, A. (2019, September). Question similarity in community question answering: A systematic exploration of preprocessing methods and models. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019) (pp. 593-601).
- Verberne, S., Krahmer, E., Hendrickx, I., Wubben, S., & van Den Bosch, A. (2018). Creating a reference data set for the summarization of discussion forum threads. Language Resources and Evaluation, 52(2), 461-483.
- Verberne, S., Krahmer, E., Wubben, S., & van den Bosch, A. (2020). Query-based summarization of discussion threads. Natural Language Engineering, 26(1), 3-29.
- Wubben, S., Krahmer, E. J., van den Bosch, A. P. J., & Verberne, S. (2016). Abstractive compression of captions with attentive recurrent neural networks.
- Wubben, S., Verberne, S., Krahmer, E. J., & van den Bosch, A. P. J. (2015). Facilitating online discussions by automatic summarization.