{"department":[{"_id":"34"},{"_id":"819"}],"citation":{"short":"J.S. Pohl, D. Assenmacher, M.V. Seiler, H. Trautmann, C. Grimme, in:  for the Advancement of Artificial Intelligence (AAAI) Association (Ed.), Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM), AAAI Press, Palo Alto, CA, USA, 2022, pp. 1–10.","ama":"Pohl JS, Assenmacher D, Seiler MV, Trautmann H, Grimme C. Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches. In: the Advancement of Artificial Intelligence (AAAI) Association  for, ed. <i>Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM)</i>. AAAI Press; 2022:1–10. doi:<a href=\"https://doi.org/10.36190/2022.91\">10.36190/2022.91</a>","bibtex":"@inproceedings{Pohl_Assenmacher_Seiler_Trautmann_Grimme_2022, place={Palo Alto, CA, USA}, title={Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches}, DOI={<a href=\"https://doi.org/10.36190/2022.91\">10.36190/2022.91</a>}, booktitle={Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM)}, publisher={AAAI Press}, author={Pohl, Janina Susanne and Assenmacher, Dennis and Seiler, Moritz Vincent and Trautmann, Heike and Grimme, Christian}, editor={the Advancement of Artificial Intelligence (AAAI) Association, for}, year={2022}, pages={1–10} }","ieee":"J. S. Pohl, D. Assenmacher, M. V. Seiler, H. Trautmann, and C. Grimme, “Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches,” in <i>Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM)</i>, 2022, pp. 1–10, doi: <a href=\"https://doi.org/10.36190/2022.91\">10.36190/2022.91</a>.","mla":"Pohl, Janina Susanne, et al. “Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches.” <i>Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM)</i>, edited by for the Advancement of Artificial Intelligence (AAAI) Association, AAAI Press, 2022, pp. 1–10, doi:<a href=\"https://doi.org/10.36190/2022.91\">10.36190/2022.91</a>.","chicago":"Pohl, Janina Susanne, Dennis Assenmacher, Moritz Vincent Seiler, Heike Trautmann, and Christian Grimme. “Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches.” In <i>Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM)</i>, edited by for the Advancement of Artificial Intelligence (AAAI) Association, 1–10. Palo Alto, CA, USA: AAAI Press, 2022. <a href=\"https://doi.org/10.36190/2022.91\">https://doi.org/10.36190/2022.91</a>.","apa":"Pohl, J. S., Assenmacher, D., Seiler, M. V., Trautmann, H., &#38; Grimme, C. (2022). Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches. In  for the Advancement of Artificial Intelligence (AAAI) Association (Ed.), <i>Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM)</i> (pp. 1–10). AAAI Press. <a href=\"https://doi.org/10.36190/2022.91\">https://doi.org/10.36190/2022.91</a>"},"type":"conference","publisher":"AAAI Press","user_id":"15504","year":"2022","author":[{"first_name":"Janina Susanne","full_name":"Pohl, Janina Susanne","last_name":"Pohl"},{"first_name":"Dennis","last_name":"Assenmacher","full_name":"Assenmacher, Dennis"},{"first_name":"Moritz Vincent","last_name":"Seiler","full_name":"Seiler, Moritz Vincent"},{"orcid":"0000-0002-9788-8282","id":"100740","first_name":"Heike","full_name":"Trautmann, Heike","last_name":"Trautmann"},{"full_name":"Grimme, Christian","last_name":"Grimme","first_name":"Christian"}],"status":"public","_id":"46303","date_created":"2023-08-04T07:11:34Z","doi":"10.36190/2022.91","abstract":[{"text":"Social media platforms are essential for information sharing and, thus, prone to coordinated dis- and misinformation campaigns. Nevertheless, research in this area is hampered by strict data sharing regulations imposed by the platforms, resulting in a lack of benchmark data. Previous work focused on circumventing these rules by either pseudonymizing the data or sharing fragments. In this work, we will address the benchmarking crisis by presenting a methodology that can be used to create artificial campaigns out of original campaign building blocks. We conduct a proof-of-concept study using the freely available generative language model GPT-Neo in this context and demonstrate that the campaign patterns can flexibly be adapted to an underlying social media stream and evade state-of-the-art campaign detection approaches based on stream clustering. Thus, we not only provide a framework for artificial benchmark generation but also demonstrate the possible adversarial nature of such benchmarks for challenging and advancing current campaign detection methods.","lang":"eng"}],"publication":"Workshop Proceedings of the 16$^th$ International Conference on Web and Social Media (ICWSM)","editor":[{"full_name":"the Advancement of Artificial Intelligence (AAAI) Association, for","last_name":"the Advancement of Artificial Intelligence (AAAI) Association","first_name":"for"}],"title":"Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches","date_updated":"2023-10-16T12:49:59Z","page":"1–10","place":"Palo Alto, CA, USA","language":[{"iso":"eng"}]}