Dear colleagues, We would like to advertise this AoIR satellite event. *Coordinated Sharing Behavior Detection Conference* *A one-day event bringing together some of the world's leading experts to showcase, discuss, and advance the state of the art in multimodal and cross-platform coordinated behavior detection.* Tuesday, 29 October 2024 University of Sheffield, Jessop Building - Room G03 - ensemble room 1 It will also be possible to attend the conference remotely. Room seats are limited to 32. To attend it is necessary to register here <https://sites.google.com/uniurb.it/csbdetectionconf/home#h.h23pvc23k73w>. The role of social media platforms during protests has been extensively documented, showing how these platforms facilitate coordination and amplify the voices of marginalized groups. However, the same tactics used by oppressed minorities can be repurposed by extremists, hate groups, trolls, and marketers. This recognition has led social media platforms, policymakers, and scholars to acknowledge the potential dangers. Consequently, platforms enforce actions against coordinated behaviors that violate community standards, with policies designed to be neutral regarding the content shared. Since 2016, there has been a shift towards focusing on behavior rather than content to combat disinformation. This strategy avoids the limitations of content-based approaches and protects platforms from accusations of arbitrating truth. The concept of "coordinated inauthentic behavior," introduced by Nathaniel Gleicher of Facebook (now Meta), adds a layer of complexity by requiring authenticity. While some ambiguity is necessary to combat adversarial tactics aimed at evading detection, the lack of clear definitions and operationalization poses significant challenges for external researchers attempting to detect coordinated behavior on social media. Scholars have developed open-source software toolkits to detect coordinated behavior, emphasizing the need to identify similar actions, such as sharing the same link or post in a closely timed and repetitive manner. The diverse forms of similarity, varying social media platforms, and evolving user behaviors make setting fixed detection thresholds difficult, often requiring case-by-case handling. The lack of universally recognized thresholds complicates the use of traditional machine learning approaches that rely on labeled datasets. In this context, our upcoming conference, part of the vera.ai project's task "Tackling Coordinated Sharing Behavior with Network Science Methods," aims to explore the origins of coordinated behavior on social media, the challenges in developing detection tools, and the frontiers of cross-platform and multimodal detection. We will also address issues related to ethics and accountability and reflect on the role of coordination in light of the emergence of generative AI. *Keynote:* Timothy Graham (Queensland University of Technology) *Speakers: *Daniel Angus (Queensland University of Technology), Felipe Bonow Soares (London College of Communication), Ahmad Zareie (University of Sheffield), Stefano Cresci (CNR), Fabio Giglietto (University of Urbino), Raquel Recuero (Universidade Federal de Pelotas/Universidade Federal do Rio Grande do Sul), Nicola Righetti (University of Urbino), Aytalina Kulichkina (University of Vienna), Daniel Thiele (Weizenbaum Institute - Freie Universität Berlin), Miriam Milzner (Weizenbaum Institute - Freie Universität Berlin), Luca Rossi (IT University of Copenhagen), Jakob Kristensen (Roskilde University Denmark) The conference is organized by the VeraAI <https://www.veraai.eu/home> consortium in partnership with SOBIGDATA++ <https://plusplus.sobigdata.eu/> and QUT Digital Media Research Center and hosted by the School of Computer Science of the University of Sheffield. Additional details and the conference schedule are available on the website <https://sites.google.com/uniurb.it/csbdetectionconf/home>. -- Giada Marino, PhD Postdoctoral Research Fellow @University of Urbino Vera.ai <https://www.veraai.eu/home> researcher I-POLHYS <https://www.ipolhys.it/> team MINe <https://mine.uniurb.it/> team Google Scholar <https://scholar.google.com/citations?user=3hdpfxMAAAAJ&hl=en> Linkedin <https://it.linkedin.com/in/giada-marino-6b12b088> Threads *@gi_hades@threads.net <http://@gi_hades@threads.net>* Blog SMSnacks <https://socialmediasnacks.tumblr.com/>