Publications
2024
Scholarly publications
Lu, Z., Wang, S., Ren, X.-L., Costas, R., & Metze, T. (2024). Influential Node Detection on Graph on Event Sequence. In Complex Networks and Their Applications XII (pp. 147-158). Springer Nature Switzerland AG. https://link.springer.com/chapter/10.1007/978-3-031-53472-0_13
Zhao, Y., Yin, K., Wang, Z., Dastani, M., & Wang, S. (2024). Decomposed Deep Q-Network for Coherent Task-Oriented Dialogue Policy Learning. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 32, 1380-1391. https://doi.org/10.1109/TASLP.2024.3357038
Hui, Y., Chekol, M., & Wang, S. (2024). Leveraging Graph Embedding for Opinion Leader Detection in Dynamic Social Networks. In T. Kliegr (Ed.), Artificial Intelligence. ECAI 2023 International Workshops: Kraków, Poland, September 30 – October 4, 2023, Proceedings, Part II (1 ed., pp. 5-22). Springer. https://doi.org/10.1007/978-3-031-50485-3_1
Zhu, C., Dastani, M., & Wang, S. (2024). A survey of multi-agent deep reinforcement learning with communication. Autonomous Agents and Multi-Agent Systems, 38(1), Article 4. https://doi.org/10.1007/s10458-023-09633-6
https://dspace.library.uu.nl/bitstream/handle/1874/435362/s10458-023-09633-6.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/435362/s10458-023-09633-6.pdf?sequence=1
2023
Scholarly publications
Zhang, C., Wang, S., Liefooghe, B., Spelt, H., Xu, J., & IJsselsteijn, W. A. (2023). Using AI Methods for Health Behavior Change. CEUR Workshop Proceedings, 3474, 1-5. https://ceur-ws.org/Vol-3474/preface4.pdf
https://dspace.library.uu.nl/bitstream/handle/1874/435714/preface4.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/435714/preface4.pdf?sequence=1
Han, S., Dastani, M., & Wang, S. (2023). Model-Based Sparse Communication in Multi-Agent Reinforcement Learning. In Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (Vol. 2023-May, pp. 439–447). (Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). https://doi.org/10.5555/3545946.3598669
https://dspace.library.uu.nl/bitstream/handle/1874/428765/3545946.3598669.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/428765/3545946.3598669.pdf?sequence=1
2022
Scholarly publications
Zhang, C., Wang, S., Tjong Kim Sang, E., Adriaanse, M. A., Tummers, L., Schraagen, M., Qi, J., Dastani, M., & Aarts, H. (2022). Spatiotemporal variations of public opinion on social distancing in the Netherlands: Comparison of Twitter and longitudinal survey data. Frontiers in Public Health, 10, 1-14. Article 856825. https://doi.org/10.3389/fpubh.2022.856825
Sporrel, K., Wang, S., Ettema, D. D. F., Nibbeling, N., Krose, B. J. A., Deutekom, M., de Boer, R. D. D., & Simons, M. (2022). Just-in-Time Prompts for Running, Walking, and Performing Strength Exercises in the Built Environment: 4-Week Randomized Feasibility Study. JMIR Formative Research, 6(8), 1-18. Article e35268. https://doi.org/10.2196/35268
Zhao, Y., Qin, H., Zhenyu, W., Zhu, C., & Wang, S. (2022). A Versatile Adaptive Curriculum Learning Framework for Task-oriented Dialogue Policy Learning. In Findings of the Association for Computational Linguistics: NAACL 2022 (pp. 711-723). Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.findings-naacl.54
https://dspace.library.uu.nl/bitstream/handle/1874/423170/2022.findings_naacl.54.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/423170/2022.findings_naacl.54.pdf?sequence=1
2021
Scholarly publications
Zhao, Y., Wang, Z., Zhu, C., & Wang, S. (2021). Efficient Dialogue Complementary Policy Learning via Deep Q-network Policy and Episodic Memory Policy. In M.-F. Moens, X. Huang, L. Specia, & S. W. Yih (Eds.), Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (pp. 4311-4323). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.emnlp-main.354
Wang, S., Zhang, C., Kröse, B., & van Hoof, H. (2021). Optimizing Adaptive Notifications in Mobile Health Interventions Systems: Reinforcement Learning from a Data-driven Behavioral Simulator. Journal of Medical Systems, 45(12), 1-8. Article 102. https://doi.org/10.1007/s10916-021-01773-0
Wang, S., Sporrel, K., van Hoof, H., Simons, M., de Boer, R. D. D., Ettema, D., Nibbeling, N., Deutekom, M., & Kröse, B. (2021). Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application: A Feasibility Study. International Journal of Environmental Research and Public Health, 18(11), 1-15. Article 6059. https://doi.org/10.3390/ijerph18116059
Sporrel, K., De Boer, R. D. D., Wang, S., Nibbeling, N., Simons, M., Deutekom, M., Ettema, D., Castro, P. C., Dourado, V. Z., & Kröse, B. (2021). The Design and Development of a Personalized Leisure Time Physical Activity Application Based on Behavior Change Theories, End-User Perceptions, and Principles From Empirical Data Mining. Frontiers in Public Health, 8, 1-19. Article 528472. https://doi.org/10.3389/fpubh.2020.528472
Sporrel, K., Nibbeling, N., Wang, S., Ettema, D., & Simons, M. (2021). Unraveling Mobile Health Exercise Interventions for Adults: Scoping Review on the Implementations and Designs of Persuasive Strategies. JMIR mHealth and uHealth, 9(1), 1-19. Article e16282. https://doi.org/10.2196/16282
Wang, S., Scheider, S., Sporrel, K., Deutekom, M., Timmer, J., & Kröse, B. J. A. (2021). What are Good Situations for Running? A Machine Learning Study using Mobile and Geographical Data. Frontiers in Public Health, 8, 1-15. Article 536370. https://doi.org/10.3389/fpubh.2020.536370
2020
Scholarly publications
Wang, S., Schraagen, M., Tjong Kim Sang, E., & Dastani, M. (2020). Public Sentiment on Governmental COVID-19 Measures in Dutch Social Media. In K. Verspoor, K. Bretonnel Cohen, M. Conway, B. de Bruijn, M. Dredze, R. Mihalcea, & B. Wallace (Eds.), Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at the 2020 Conference on Empirical Methods in Natural Language Processing Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2020.nlpcovid19-2.17
https://dspace.library.uu.nl/bitstream/handle/1874/414714/2020.nlpcovid19_2.17.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/414714/2020.nlpcovid19_2.17.pdf?sequence=1
Jiang, B., Hou, J., Zhou, W., Yang, C., Wang, S., & Pang, L. (2020). METNet: A Mutual Enhanced Transformation Network for Aspect-based Sentiment Analysis. In Proceedings of the 28th International Conference on Computational Linguistics (pp. 162-172). International Committee on Computational Linguistics. https://doi.org/10.18653/v1/2020.coling-main.14
Jiang, B., Zhou, W., Yang, J., Yang, C., Wang, S., & Pang, L. (2020). PEDNet: A Persona Enhanced Dual Alternating Learning Network for Conversational Response Generation. In D. Scott, N. Bel, & C. Zong (Eds.), Proceedings of the 28th International Conference on Computational Linguistics (pp. 4089-4099). International Committee on Computational Linguistics. https://doi.org/10.18653/v1/2020.coling-main.361
QI, JI., Bloemen, V., Wang, S., van Wijk, J., & van de Wetering, H. (2020). STBins: Visual Tracking and Comparison of Multiple Data Sequences Using Temporal Binning. IEEE Transactions on Visualization and Computer Graphics, 26(1), 1054-1063. https://doi.org/10.1109/tvcg.2019.2934289
2018
Scholarly publications
Wang, S., Songhori, M. J., Chang, S., & Terano, T. (2018). How triangle structure in inter-firm human network affects bankruptcy evolution: An agent-based simulation study with real and artificial data. In D. N. Cassenti (Ed.), Advances in Human Factors in Simulation and Modeling - Proceedings of the AHFE 2017 International Conference on Human Factors in Simulation and Modeling, 2017 (pp. 285-296). (Advances in Intelligent Systems and Computing; Vol. 591). Springer Verlag. https://doi.org/10.1007/978-3-319-60591-3_26
Wang, S., Timmer, J. A., Scheider, S., Sporrel, K., Akata, Z., & Kroese, B. (2018). A Data-driven Study on Preferred Situations for Running. In UbiComp 2018 Adjunct Proceedings
2017
Scholarly publications
Wang, S., Moise, I., Helbing, D., & Terano, T. (2017). Early Signals of Trending Rumor Event in Streaming Social Media. In Proceedings - International Computer Software and Applications Conference (pp. 654-659). (Proceedings - International Computer Software and Applications Conference; Vol. 2). IEEE Computer Society Press. https://doi.org/10.1109/COMPSAC.2017.115
Tan, L., Wang, S., & Terano, T. (2017). Study on the social networks based on Japanese social events from name card data. In Y. Demazeau, J. Gao, G. Xu, J. Kozlak, K. Muller, I. Razzak, H. Chen, & Y. Gu (Eds.), Proceedings of 4th International Conference on Behavioral, Economic, and Socio-Cultural Computing, BESC 2017 (Vol. 2018-January, pp. 1-5). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BESC.2017.8256390
2016
Scholarly publications
Wang, S., Songhori, M. J., Chang, S., & Terano, T. (2016). The impact of human relationship on bankruptcy-related evolution of inter-firm trade network. In T. M. Roeder, P. I. Frazier, R. Szechtman, & E. Zhou (Eds.), 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016 (Vol. 0, pp. 3405-3416). Article 7822371 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC.2016.7822371
2015
Scholarly publications
Wang, S., & Terano, T. (2015). Detecting rumor patterns in streaming social media. In F. Luo, K. Ogan, M. J. Zaki, L. Haas, B. C. Ooi, V. Kumar, S. Rachuri, S. Pyne, H. Ho, X. Hu, S. Yu, M. H.-I. Hsiao, & J. Li (Eds.), Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015 (pp. 2709-2715). Article 7364071 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2015.7364071