[Air-L] #AoIR2024 Satellite Conference on Coordinated Sharing Behavior Detection

[Marino, Giada]

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 at threads.net
<http://@gi_hades@threads.net>*
Blog SMSnacks <https://socialmediasnacks.tumblr.com/>