Disinformation and Coordinated Inauthentic Behavior
Nowadays, social networking platforms are a crucial component of the public sphere, fostering discussions and influencing the public perception for a myriad of topics including politics, health, climate change, economics, migration, to name but a few. On the one hand, this represents an unprecedented opportunity to discuss and propose new ideas, democratizing information and giving voice to the crowds. On the other hand however, new socio-technical issues arise.
Among the most pressing issues is the spread of fictitious and low-quality information (e.g., fake news, rumors, hoaxes). These questionable means are often used to influence the opposing side about controversial and polarizing topics, or simply to sow discord and erode trust in governments, institutions and societies. The spread of low-quality information is sometimes carried out by groups of coordinated or automated accounts that pollute and tamper with our social environments by injecting and resharing a large number of targeted messages. These issues are currently exacerbated by the recent advances in AI that have made it easy and convenient to fabricate plausible texts, to create high-quality images of non-existing people, and to impersonate public characters in videos (e.g., deepfakes), at large. All these aspects jointly contribute to making our online social ecosystems the ideal landscape for deceit and manipulation. Therefore, prompt responses are expected from decision makers, scholars and practitioners in order to limit the spread and impact of these ailments.
The International Workshop on “Information Disorders: Fake News and Coordinated Inauthentic Behaviors (DisInfo’20)” focuses on the study, modeling, and characterization of all challenges related to mis- and dis-information, fake news, coordinated inauthentic behavior and information operations.
Areas of interest to DisInfo’20 include, but are not limited to, the following:
- Information diffusion models for understanding and thwarting the spread of low-quality information;
- Automatic techniques for the detection of propaganda and fake news;
- Understanding and detection of information operations;
- Characterization and detection of coordinated inauthentic behavior;
- Novel techniques for detecting malicious accounts (e.g., bots, cyborgs and trolls);
- Graph mining and network analysis approaches for studying polarized communities and for reducing polarization;
- Metrics, tools and methods for measuring the impact of fake news and of coordinated inauthentic behaviors;
- Detection of deepfake text, image, and video manipulation;
- Fake news and coordinated inauthentic behavior in infodemics;
- Case-studies on the spread and impact of fake news in controversial topics such as politics, health, climate change, economics, migration;
- Impact/Harm of misinformation on society;
- Types of misinformation: Rumour, Fake news;
- Studies (psychological or data analytics) related to misinformation spreaders.
Extended abstract submission: September 11, 2020 (submission link)
Notification: September 23, 2020
Workshop: October 06, 2020
We invite submissions of extended abstracts addressing at least one of the workshop topics, from the perspective of theoretical analyses, algorithms, new resources, tools and systems, practical use cases and applications. Submissions can describe past published work that is particularly relevant to the workshop, as well as ongoing unpublished work.
Submitted extended abstracts should be at maximum 2 pages long (all considered, thus including possible figures, tables, references, etc.) and should stick to the SocInfo’20 template and format (Springer LNCS). Submissions should not be anonymized, as the review process will be single-blind. Each submission will be evaluated by members of the technical program committee. Authors of selected abstracts will be invited for a short presentation (15 minutes each) during the workshop and selected abstracts will be made available on this website.
Submissions should be made via easychair.
|09:30||10:00||First Keynote speech (25’+5’Q)|
|10:00||10:45||Contributed talks (3 presentations of 12’+3’Q)|
|11:00||11:30||Second Keynote speech (25’+5’Q)|
|10:00||10:45||Contributed talks (3 presentations of 12’+3’Q)|
Invited Keynote Speakers
Keynote title: Detection of Propaganda in the News
Preslav Nakov is a Principal Scientist at the Qatar Computing Research Institute, HBKU. His research interests include computational linguistics and natural language processing, disinformation, fake news and bias detection, fact-checking, machine translation, question answering, sentiment analysis, lexical semantics, Web as a corpus, and biomedical text processing. He is the PI of the QCRI mega-project Tanbih (http://tanbih.qcri.org/), which aims to limit the effect of “fake news”, propaganda and media bias by making users aware of what they are reading. He is also the lead-PI of a QCRI-MIT collaboration project on Arabic Speech and Language Processing for Cross-Language Information Search and Fact Verification (co-PI, 2016-2018; Lead-PI, 2018-present), and he was a co-PI of another QCRI-MIT collaboration project on Speech and Language Processing for Arabic (2013-2016). Preslav Nakov received a PhD degree in Computer Science from the University of California at Berkeley (supported by a Fulbright grant and a UC Berkeley fellowship), and an MSc degree from the Sofia University. He was a Research Fellow at the National University of Singapore (2008-2011), an honorary lecturer in the Sofia University (2008, 2014-present), research staff at the Bulgarian Academy of Sciences (2008), and a visiting researcher at the University of Southern California, Information Sciences Institute (2005). Preslav Nakov co-authored a Morgan & Claypool book on Semantic Relations between Nominals, two books on computer algorithms, and many research papers in top-tier conferences and journals. He received the Young Researcher Award at RANLP’2011. He was also the first to receive the Bulgarian President’s John Atanasoff award. Preslav Nakov is President of ACL SIGLEX, the Special Interest Group (SIG) on the Lexicon of the Association for Computational Linguistics (ACL). He is also Secretary of SIGSLAV, the ACL SIG on Slavic Natural Language Processing. He also serves on the advisory board of EACL. He is an Action Editor of the Transactions of the Association for Computational Linguistics (TACL) journal, a Member of the Editorial Board of Computer Speech and Language (CSL), of the Journal of Natural Language Engineering (NLE) and of the Language Science Press Book Series on Phraseology and Multiword Expressions, an Associate Editor of Frontiers in Artificial Intelligence journal (Language and Computation Section) and of the AI Communications journal. He served on the program committees of the major conferences and workshops in Computational Linguistics. He co-chaired SemEval 2014-2016 and was a (senior) area co-chair of ACL, EMNLP, NAACL-HLT, and *SEM, a Senior PC member of AAAI and IJCAI, a shared task co-chair of IJCNLP, a tutorial co-chair of ACL, and a workshop co-chair of COLING. Preslav Nakov’s research is featured in 100+ news outlets, including Forbes, Boston Globe, Aljazeera, MIT Technology Review, Science Daily, Popular Science, Fast Company, The Register, WIRED, and Engadget, among others.
Giovanni Da San Martino is a Scientist at Qatar Computing Research Institute since 2014. His research interests are at the intersection of machine learning and natural language processing, with applications to community question answering and news analysis. He has co-authored more than 60 papers on those subjects. Prior to joining QCRI, he has been a Postdoc at the University of Padova, Italy and received his PhD in computer science from the University of Bologna. Since 2018, he is involved in the Tanbih and Catalyst projects, both concerning the building of intelligent tools for the analysis of the news; the projects are in collaboration with MIT-CSAIL and media partners such as Al Jazeera and Associated Press, respectively. In those projects, his focus is in building automatic systems to detect the use of propaganda in written texts. He is member of the Editorial Board of Information Processing & Management journal and review editor for the Frontiers in Artificial Intelligence journal; he has served as area chair fo ACL’19 and ACL’20 and he is reviewing for several journals and top-tier conferences in machine learning (NEURIPS, TNNLS, IJCAI, AAAI, Neural Networks) and natural language processing (TACL, NAACL). He will serve as general chair for CLEF 2022 and he is organiser of several events around the topic of propaganda detection and misinformation: workshops (CLEF’19, CLEF’20, SocInfo’19, NLP4IF’19, NLP4IF’20), hackathons and shared tasks (“Hack the news datathon”, EMNLP’19, SemEval2020), tutorials (IJCAI’20 and EMNLP’20) and summer schools (RUSSIR’20).
Keynote title: Information Spreading on Social Media
Antonio Scala holds a Master degree in Physics and Computer Science at the University of Napoli “Federico II” and a PhD in condensed matter Physics at the Boston University. He is now Senior research scientist at the CNR Institute for Complex Systems (University of Roma “La Sapienza”), associate professor at IMT Alti Studi Lucca and research fellow at LIMS the London Institute for Mathematical Sciences. His main skills are Statistical Physics and Computational Physics; he has published papers on percolation, disordered systems, pattern formation, metastable liquids, glassy systems, energy landscapes, protein folding, complex networks, event-driven algorithms, complexity in economics, network medicine, infrastructural networks. Together with G. D’Agostino, he is the organizer of the workshop series “Networks of networks” on Systemic Risk and Infrastructural Inter-dependencies. His current research focuses on complex infrastructural networks and on computational social science.
Stefano Cresci received his PhD in Information Engineering from the University of Pisa in 2018. He is a Researcher at the Institute of Informatics and Telematics (IIT) of the National Research Council (CNR) of Italy. His interests encompass data science, social media analysis, and big social data, with a focus on misinformation, anomalous behavior detection, and crisis informatics. Stefano currently serves in the program committee of several top-level international conferences, such as ICWSM, IJCAI, ACM WebSci, IC2S2, ISCRAM, and more. In 2018, he was selected among the winners of a SAGE Ocean Concept Grant. In 2019, he won the IEEE Computer Society Italy Section Chapter 2018 PhD Thesis Award and the IEEE Next-Generation Data Scientist Award. In 2020, he was selected and invited to participate in the 8th Heidelberg Laureate Forum.
Rajesh Sharma is presently working as a senior researcher of Information Systems at the Institute of Computer Science at the University of Tartu, Estonia. The position is equivalent to Associate Professor in the Estonian Education System. Dr. Sharma’s interests include Big data analytics, especially in the domain of Social Media and Social Network Analysis. He has published papers in IEEE Big data and IEEE/ACM ASONAM conferences and in journals such as International Journal of Data Science and Analytics, IEEE Transactions on Network Science and Engineering, Journal of Social Network Analysis and Mining. In particular, he has published papers on (mis)information diffusion on single and multilayer networks. He is serving on the advisory board members of an IMF project about detecting conflicts of interest in public procurement, and also serves as a TPC for ASONAM, Complex Networks, and SocInfo Conferences. He was an invited speaker at the Digital Humanities Workshop, Estonia. In the past, he was part of SoBigData (H2020) project and presently working on SoBigData research infrastructure project and InWeGe (EU commission project related to the gender pay gap in Estonia). He is also involved in an Industrial project with Swedbank.
Walter Quattrociocchi is head of the Laboratory of Data and Complexity at Ca’Foscari University of Venice, where he is Assistant Professor (Tenure Track) in Computer Science and currently qualified for associate professorship. His research interests include data science, network science, cognitive science, and data-driven modeling of dynamic processes in complex networks. His activity focuses on the data-driven modeling of social dynamics such as (mis)information spreading and the emergence of collective phenomena. Dr Quattrociocchi has published extensively in peer reviewed conferences and journals including PNAS. The results of his research in misinformation spreading have informed the Global Risk Report 2016 and 2017 of the World Economic Forum and have been covered extensively by international media including Scientific American, New Scientist, The Economist, The Guardian, New York Times, Washington Post, Bloomberg, Fortune, Poynter and The Atlantic). He published two books: “Misinformation. Guida alla società dell’informazione e della credulità” (Franco Angeli) and “Liberi di Crederci. Informazione, Internet e Post Verità” with Codice Edizioni for the dissemination of his results. In 2017 Dr Quattrociocchi was the coordinator of the round table on Fake News and the role of Universities and Research to contrast fake news chaired by the President of Italy’s Chamber of Deputies Mrs Laura Boldrini. Since 2018 he is Scientific Advisor of the Italian Communication Authority (AGCOM). Dr Quattrociocchi is regularly invited for keynote speeches and guest lectures at major academic and other organizations.
Dr. Maurizio Tesconi (PhD) is a researcher in Computer Science and leads the Web Application for the Future Internet Lab at the Institute of Informatics and Telematics of CNR. His research interests include big data, web mining, social network analysis, and visual analytics within the context of Open Source Intelligence.
He participated in the EU co-funded CAPER project, dealing with the creation of a common platform for the prevention of organized crime, and the OpeNER project, for reusing existing language resources and data sets to provide a set of opinion mining and sentiment analysis tools. He is responsible for the SoS project, an internal project aiming to exploit users of social media platforms as sensors in the detection of occurring real events.
Dr. Tesconi led the IIT-CNR team of the project CASSANDRA, focused on New Psychoactive Substance detection and analysis. He is also part of the permanent team of the European Laboratory on Big Data Analytics and Social Mining (www.sobigdata.eu) and of the EU funded project SoBigData Research Infrastructure project, performing advanced research and analyses on the emerging challenges posed by big data and he is teaching Cyber Intelligence at the Master in Cyber Security of the University of Pisa.