[{"publication":"Proceedings of the Florida Artificial Intelligence Research Society Conference","citation":{"short":"D. Assenmacher, L. Adam, H. Trautmann, C. Grimme, in: Proceedings of the Florida Artificial Intelligence Research Society Conference, Florida, USA, 2020.","chicago":"Assenmacher, D, L Adam, Heike Trautmann, and C Grimme. “Towards Real-Time and Unsupervised Campaign Detection in Social Media.” In <i>Proceedings of the Florida Artificial Intelligence Research Society Conference</i>. Florida, USA, 2020.","ieee":"D. Assenmacher, L. Adam, H. Trautmann, and C. Grimme, “Towards Real-Time and Unsupervised Campaign Detection in Social Media,” 2020.","apa":"Assenmacher, D., Adam, L., Trautmann, H., &#38; Grimme, C. (2020). Towards Real-Time and Unsupervised Campaign Detection in Social Media. <i>Proceedings of the Florida Artificial Intelligence Research Society Conference</i>.","bibtex":"@inproceedings{Assenmacher_Adam_Trautmann_Grimme_2020, place={Florida, USA}, title={Towards Real-Time and Unsupervised Campaign Detection in Social Media}, booktitle={Proceedings of the Florida Artificial Intelligence Research Society Conference}, author={Assenmacher, D and Adam, L and Trautmann, Heike and Grimme, C}, year={2020} }","ama":"Assenmacher D, Adam L, Trautmann H, Grimme C. Towards Real-Time and Unsupervised Campaign Detection in Social Media. In: <i>Proceedings of the Florida Artificial Intelligence Research Society Conference</i>. ; 2020.","mla":"Assenmacher, D., et al. “Towards Real-Time and Unsupervised Campaign Detection in Social Media.” <i>Proceedings of the Florida Artificial Intelligence Research Society Conference</i>, 2020."},"abstract":[{"lang":"eng","text":"The detection of orchestrated and potentially manipulative campaigns in social media is far more meaningful than an- alyzing single account behaviour but also more challenging in terms of pattern recognition, data processing, and com- putational complexity. While supervised learning methods need an enormous amount of reliable ground truth data to find rather inflexible patterns, classical unsupervised learn- ing techniques need a lot of computational power to handle large amount of data. This makes them infeasible for real- time analysis. In this work, we demonstrate the applicability of text stream clustering for the real-time detection of coordi- nated campaigns."}],"date_created":"2023-08-04T07:29:36Z","place":"Florida, USA","type":"conference","department":[{"_id":"34"},{"_id":"819"}],"title":"Towards Real-Time and Unsupervised Campaign Detection in Social Media","year":"2020","status":"public","author":[{"full_name":"Assenmacher, D","last_name":"Assenmacher","first_name":"D"},{"last_name":"Adam","first_name":"L","full_name":"Adam, L"},{"full_name":"Trautmann, Heike","orcid":"0000-0002-9788-8282","first_name":"Heike","last_name":"Trautmann","id":"100740"},{"last_name":"Grimme","first_name":"C","full_name":"Grimme, C"}],"date_updated":"2023-10-16T12:59:10Z","_id":"46319","language":[{"iso":"eng"}],"user_id":"15504"}]