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MAD 2022 : 1st Workshop on Multimedia AI against Disinformation


When Jun 27, 2022 - Jun 30, 2022
Where Newark, NJ, USA
Submission Deadline Feb 27, 2022
Notification Due Mar 30, 2022
Categories    artificial intelligence   NLP   text mining   natural language processing

Call For Papers

MAD 2022
1st Workshop on Multimedia AI against Disinformation
@ ACM International Conference on Multimedia Retrieval - ICMR 2022
Newark, NJ, USA, June 27-30, 2022

*** Call for papers ***
* Paper submission due: February 17, 2022
* Acceptance notification: March 30, 2022
* Camera-ready papers due: TBD
* Workshop @ ICMR 2022: TBD/June 27-30, 2022

Disinformation spreads easily in online social networks and is
propagated by social media actors and network communities to achieve
specific (mostly malevolent) objectives. Disinformation has
deleterious effects on users’ real lives since it distorts their
points of view regarding societally-sensitive topics, such as
politics, health or religion. Ultimately, it has a negative effect on
the very fabric of democratic societies and should be fought against
via an effective combination of human and technical means.

Disinformation campaigns are increasingly powered by advanced AI
techniques and a lot of effort was put into the detection of fake
content. While important, this is only a piece of the puzzle if one
wants to address the phenomenon in a comprehensive manner. Whether a
piece of information is considered fake or true often depends on the
temporal and cultural contexts in which it is interpreted. This is for
instance the case for scientific knowledge, which evolves at a fast
pace, and whose usage in mainstream content should be updated

Multimedia content is often at the core of AI-assisted disinformation
campaigns. Their impact is directly related to the perceived
credibility of their content. Significant advances related to the
automatic generation/manipulation of each modality were obtained with
the introduction of dedicated deep learning techniques. Visual content
can be tampered with in order to produce manipulated but realistic
versions of it. Synthesized speech has attained a high quality level
and is more and more difficult to distinguish from the actual voice.
Deep language models learned on top of huge corpora allow the
generation of text which resembles that written by humans. Combining
these advances has the potential to boost the effectiveness of
disinformation campaigns. This combination is an open research topic
which needs to be addressed in order to reduce the effects of
disinformation campaigns. This workshop welcomes contributions related
to different aspects of AI-powered disinformation.

Topics of interest include but are not limited to:
- Disinformation detection in multimedia content (video, audio, texts, images)
- Multimodal verification methods
- Synthetic and manipulated media detection
- Multimedia forensics
- Disinformation spread and effects in social media
- Analysis of disinformation campaigns in societally-sensitive domains
(e.g., politics, health)
- Explaining disinformation to non-experts
- Disinformation detection technologies for non-expert users
- Dataset sharing and governance in AI for disinformation
- Temporal and cultural aspects of disinformation
- Datasets for disinformation detection and multimedia verification
- Multimedia verification systems and applications
- System fusion, ensembling and late fusion techniques
- Benchmarking and evaluation frameworks
- Open resources, e.g., datasets, tools

*** Submission guidelines ***
To submit your contribution, please adhere strictly to the ACM ICMR
instructions available here

*** Organizing committee ***
Bogdan Ionescu, Politehnica University of Bucharest, Romania
Giorgos Kordopatis-Zilos, Centre for Research and Technology Hellas,
Thessaloniki, Greece
Symeon Papadopoulos, Centre for Research and Technology Hellas,
Thessaloniki, Greece
Adrian Popescu, CEA LIST, Saclay, France
Luca Cuccovillo, Fraunhofer IDMT, Germany

On behalf of the organizers,

Bogdan Ionescu

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