Shared Tasks

Important Dates

  • May 10, 2023: Early bird software submission phase (optional)
  • June 10, 2023: Software submission deadline (extended, was May 29)
  • June 05, 2023: Participant paper submission Midnight CEST [guidelines] [submission] [template (use this one, not the one from CLEF]
  • June 23, 2023: Peer review notification
  • July 07, 2023: Camera-ready participant papers submission Midnight CEST
  • tba: Early bird conference registration
  • September 18-21, 2023: Conference

The timezone of all deadlines is Anywhere on Earth.


Yiannis Kompatsiaris
Behavioural and Policy Aspects of Online Disinformation
Director of CERTH-ITI and Head of Multimedia Knowledge and Social Media Analytics Lab Technical

Recent technological developments and social events have contributed to a constant increase in online disinformation of various forms making it a long-lasting challenge of immense scale and complexity. Disinformation is a significant technological and social challenge, which affects key societal values including Democracy, Public Health and Peace. Apart from technology, It depends on various dimensions such as policies, business models, education, digital literacy and human behaviour. Focusing on visual disinformation, including manipulated photos/video, deepfakes, visuals out of context and false connections, a variety of approaches and tools are needed in order to address this challenge. In this talk, after a general introduction and overview, I will be presenting our lab’s efforts in this area, across three main directions: approaches which take into account content, context and network-based information. It will include media forensics, deepfake detection and reverse image and video search approaches together with tools already used by journalists and fact-checkers. Key challenges and additional aspects such as actual operational settings, human behaviour, education and policy issues will also be covered.

Dr. Ioannis (Yiannis) Kompatsiaris is the Director of CERTH-ITI and the Head of Multimedia Knowledge and Social Media Analytics Laboratory. His research interests include ΑΙ/ML for Multimedia, Semantics (multimedia ontologies and reasoning), Social Media and Big Data Analytics, Multimodal and Sensors Data Analysis, Human Computer Interfaces, e- Health, Cultural, Media/Journalism and Security applications. He is the co-author of 178 papers in refereed journals, 63 book chapters, 8 patents and 560 papers in international conferences. Since 2001, Dr. Kompatsiaris has participated in 88 National and European research programs, in 31 of which he has been the Project Coordinator. He has also been the PI in 15 contracts from the industry. He has been the co-chair of various international conferences and workshops including the 13th IEEE Image, Video, and Multidimensional Signal Processing (IVMSP 2018) Workshop and has served as a regular reviewer, associate and guest editor for a number of journals and conferences currently being an associate editor of IEEE Transactions on Image Processing. He is a member of the National Ethics and Technoethics Committee, the Scientific Advisory Board of the CHIST-ERA funding programme and an elected member of the IEEE Image, Video and Multidimensional Signal Processing – Technical Committee (IVMSP – TC). He is a Senior Member of IEEE and ACM. Since January 2014, he is a co-founder of the Infalia private company, a high-tech SME focusing on data intensive web services and applications.

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Alejandro Martin
Detecting and Disrupting Disinformation: Social Network Analysis and Natural Language Processing
Associate professor at Universidad Politécnica de Madrid

Detecting and Disrupting Disinformation: Social Network Analysis and Natural Language Processing In recent years, social network analysis has become an increasingly important tool in understanding and combating the spread of disinformation. By examining the patterns of information flow, we can identify the sources and pathways through which false information spreads and take steps to prevent its dissemination. However, the problem of disinformation is not limited to the propagation of already-existing false information; AI is now being used to generate convincing fake news, amplifying the spread of disinformation and making it increasingly difficult to distinguish fact from fiction. Despite the challenges posed by AI-generated false content, AI can also play an important role in the fight against disinformation. Through the use of natural language processing techniques, we can reveal key characteristics of false information, enabling us to more effectively identify and combat disinformation campaigns. Additionally, machine learning algorithms can be used to identify patterns of disinformation and to distinguish between false and genuine content. In this talk, we will explore the current state of the art in social network analysis and AI with respect to disinformation. We will present examples of different models and architectures that have been developed to combat disinformation, including case studies of real-world disinformation campaigns. By combining the strengths of social network analysis and AI (i.e., large language models), we can develop more effective tools for combating the spread of disinformation, protecting the integrity of public discourse, and upholding the principles of truth and accuracy in our information ecosystem.

Dr. Alejandro Martín is Associate Professor at Universidad Politécnica de Madrid. His main research interests are Deep Learning, Cybersecurity, and Natural Language Processing. He has been visiting researcher at the University of Kent. Besides, he has participated in an important number of international conferences as a reviewer and organizer, as an Associate Editor and Guest Editor in international journals, and in a large number of research projects. He is currently leading different research focused on the fight against misinformation through Natural Language Processing techniques and Social Network Analysis.

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PAN's program is part of the CLEF 2023 conference program. All times are Eastern European Summer Time - EEST.

Monday, September 18
11.20-13.00CLEF Session: Lab Overviews (PAN, BioAsq, eRisk, SimpleText, LifeCLEF)
16:10-17:40Keynote and Lab Session, Chair: Paolo Rosso
16:10-17:10Keynote: Behavioural and Policy Aspects of Online Disinformation
Yiannis Kompatsiaris
17:10-17:35Overview: Profiling Cryptocurrency Influencers
Mara Chinea-Rios, Ian Borrego-Obrador, Marc Franco-Salvador, Francisco Rangel, and Paolo Rosso
17:35-17:40Best System Award: Profiling Cryptocurrency Influencers
17:40-19:00Joint Poster Session
Tuesday, September 19
09:30-11:00Keynote and Lab Session, Chair: Efstathios Stamatatos
09:30-10:30Keynote: Detecting and Disrupting Disinformation: Social Network Analysis and Natural Language Processing
Alejandro Martin
10:30-10:45Reshape or Update? Metric Learning and Fine-tuning for Low-Resource Influencer Profiling
Areg Sarvazyan
10:45-11:00Integrating Fine-Tuned Language Models and Entailment-Based Approaches for Low-Resource Tweet Classification
Emilio Villa Cueva
14:00-15:30Lab Session, Chair: Matti Wiegmann
14:00-14:30Overview: Authorship Verification
Efstathios Stamatatos and Krzysztof Kredens and Piotr Pezik and Annina Heini and Janek Bevendorff and Benno Stein and Martin Potthast
14:30-15:00Heterogeneous-Graph Convolutional Network for Authorship Verification
Andric Valdez-Valenzuela, Jorge Alfonso Martinez-Galicia, Helena Gómez-Adorno
15:00-15:30Stylometric and Neural Features Combined Deep Bayesian Classifier for Authorship Verification
Yitao Sun, Svetlana Afanaseva, Kailash Patil
16:00-17:30Lab Session, Chair: Benno Stein
16:00-16:20Overview: Multi-Author Writing Style Analysis
Eva Zangerle, Maximilian Mayerl, Martin Potthast, and Benno Stein
16:20-16:30Supervised Contrastive Learning for Multi-Author Writing Style Analysis
Zhanhong Ye, Changle Zhong, Haoliang Qi, and Yong Han
16:30-16:35Enhancing Writing Style Change Detection using Transformer-based Models and Data Augmentation
Ahmad Hashemi and Wei Shi
16:35-16:40ARC-NLP at PAN 23: Transition-Focused Natural Language Inference for Writing Style Detection
Izzet Emre Kucukkaya, Umitcan Sahin, and Cagri Toraman
16:40-16:45Authorship verification machine learning methods for Style Change Detection in texts
Gianni Jacobo, Valeria Dehesa, Damián Rojas, and Helena Gómez-Adorno
16:45-17:05Overview: Trigger Detection
Matti Wiegmann and Magdalena Wolska and Benno Stein and Martin Potthast
17:05-17:15ARC-NLP at PAN 2023: Hierarchical Long Text Classification for Trigger Detection
Umitcan Sahin, Izzet Emre Kucukkaya, and Cagri Toraman
17:15-17:25FoSIL at PAN’23: Trigger Detection with a Two Stage Topic Classifier
Jenny Felser, Christoph Demus, Dirk Labudde, and Michael Spranger

Participation Modalities

Submissions to PAN 2023 are now closed.

Organizing Committee