Understanding Citizens' Vulnerabilities to Disinformation and Data-Driven Propaganda

Disinformation strategies have evolved from “hack and dump” cyber-attacks, and randomly sharing conspiracy or made-up stories, into a more complex ecosystem where narratives are used to feed people with emotionally charged true and false information, ready to be “weaponised” when necessary. Manipulated information, using a mix of emotionality and rationality, has recently become so pervasive and powerful to the extent of rewriting reality, where the narration of facts (true, partial or false) counts more than the facts themselves. Every day, an incredible amount of information is constantly produced on the web. Its diffusion is driven by algorithms, originally conceived for the commercial market, and then maliciously exploited for manipulative purposes and to build consensus. Citizens' vulnerability to disinformation operations is not only the result of the threats posed by hostile actors or psychometric profiling - which can be seen as both exploiters and facilitators - but essentially due to the effect of three different factors: Information overload; Distorted public perceptions produced by online platforms algorithms built for viral advertising and user engagement; The complex iteration of fast technology development, globalisation, and post-colonialism, which have rapidly changed the rules-based international order. In rapidly and dynamically evolving environments, increasing citizens' resilience against malicious attacks is, ultimately, of paramount importance to protect our open democratic societies, social values and individual rights and freedoms.JRC.E.7-Knowledge for Security and Migratio

Event-based surveillance during EXPO Milan 2015. Rationale, tools, procedures, and initial results

More than 21 million participants attended EXPO Milan from May to October 2015, making it one of the largest protracted mass gathering events in Europe. Given the expected national and international population movement and health security issues associated with this event, Italy fully implemented, for the first time, an event-based surveillance (EBS) system focusing on naturally occurring infectious diseases and the monitoring of biological agents with potential for intentional release. The system started its pilot phase in March 2015 and was fully operational between April and November 2015. In order to set the specific objectives of the EBS system, and its complementary role to indicator-based surveillance, we defined a list of priority diseases and conditions. This list was designed on the basis of the probability and possible public health impact of infectious disease transmission, existing statutory surveillance systems in place, and any surveillance enhancements during the mass gathering event. This article reports the methodology used to design the EBS system for EXPO Milan and the results of 8 months of surveillance

COVID-19 news monitoring with Medical Information System (Medisys)

Dataset of metadata created with Europe Media Monitor (EMM)/Medical Information System (MediSys) processing chain from news articles. MEDISYS is a media monitoring system providing event-based surveillance to rapidly identify potential public health threats using information from media reports. The system displays only those articles with interest to public health (e. g. diseases, plant pests, psychoactive substances), analyses news reports and warns users with automatically generated alerts. This dataset has a focus on Covid-19. It provides a large set of metadata automatically extracted from news articles related to Covid -19, stored as rss/xml format. It is publicly available, and anyone can build applications on top of that. The current version contains 4 months of news articles, from December 2019 to April 2020, which corresponds to more than 6 Million news articles. There is one zip file per month, containing the whole metadata information. As a example, the biggest month is March 2020, it contains 4.1 million news articles, from 76 different languages, 36 million entity occurrences (person names, organization names, location names, …), 15 million dates, 0.8 million quotations. The information processed by MediSys is derived from the Europe Media Monitor (EMM). The freely accessible Europe Media Monitor (EMM) is a fully automatic system that analyses on-line media. It gathers and aggregates about 300,000 news articles per day from news portals world-wide in up to 80 languagesJRC.I.3-Text and Data Minin

Media Monitoring of Public Health Threats with MedISys

The Medical Information System (MedISys) is a fully automatic event-based surveillance system that monitors reporting on infectious diseases in man and animals, chemical, biological, radiological and nuclear (CBRN) threats, plant health and food & feed contaminations on the internet. The system retrieves news articles from specialised official and unofficial medical sites, general news media and selected blogs, categorizes all incoming articles according to pre-defined multilingual categories, identifies known names such as organizations, persons and locations, extracts events, clusters news articles and calculates statistics to detect emerging threats. Users can screen the categorized articles and display world maps highlighting event locations together with statistics on the reporting of health threats, countries and combinations thereof. Articles can be further filtered by language, news source, and country. Analysts can use a collaborative tool called NewsDesk to further refine the selection of automatically retrieved articles and create reports or deliver notifications via e-mail or SMS.JRC.G.2-Global security and crisis managemen

EMM: Supporting the Analyst by Turning Multilingual Text into Structured Data

All information-seeking professionals need to sieve through large amounts of text to retrieve the information they need so that they can stay up-to-date of develop-ments in their field. Language Technology tools can help make the analyst’s work more efficient by increasing the amount of data analysed and by speeding up the process. Software tools applied to big data may additionally provide a bird’s view of trends and data distributions not easily visible to the human reader. The European Commission’s Joint Research Centre (JRC) has developed the Europe Media Monitor (EMM) family of applications, which aims to provide solutions for the daily media monitoring needs of a large variety of users working in diverse fields. EMM gathers and analyses hundreds of thousands of news articles every day in up to seventy languages. Due to the large scale of the effort, EMM can track topics, detect trends and act as an early warning tool. In this chapter, we present the functionality and the benefits of EMM’s news analysis capacity, but we also aim to make the reader aware of the potential dangers of automated large-scale media monitoring. The EMM team makes available for free a number of linguistic tools and resources that can be used by information specialists to improve their own analysis of large sets of textual data.JRC.I.3-Text and Data Minin

Collection And Analysis Of Open Source News For Information Awareness And Early Warning in Nuclear Safeguards

Acquisition and analysis of open source information plays an increasingly important role in the IAEA’s move towards a safeguards system, in which safeguards decisions are based on all information known about a State. The growing volume of open source information poses significant challenges. Meeting these challenges requires development of technology and tools that effectively collect relevant information, filter out "noise", organize valuable information in a clear and accessible manner and assess its relevance. In this context, IAEA’s Division of Information Management (SGIM) and the EC’s Joint Research Centre (JRC) are currently implementing a joint project to advance the effectiveness and efficiency of IAEA’s workflow for open source information collection and analysis. The objective is to provide tools supporting SGIM in the production of the SGIM Open Source Highlights, which is a daily news brief consisting of the most pertinent news stories relevant to safeguards and non-proliferation. The process involves the review and selection of hundreds of articles from a wide array of specifically selected sources. The joint activity exploits JRC’s Europe Media Monitor (EMM) and NewsDesk applications: EMM automatically collects and analyses news articles from a pre-defined list of websites, and NewsDesk allows an analyst to manually select the most relevant articles from the EMM stream for further processing. The paper discusses IAEA’s current workflow for the production of SGIM Open Source Highlights and describes the capabilities of EMM and NewsDesk. It then provides an overview of the joint activities since the project started in 2011, which were focused on testing and evaluating the EMM/NewsDesk for IAEA needs. Finally, it proposes a new workflow based on EMM/NewsDesk, which supports a safeguards system that is fully information driven with an effective and efficient process of collecting and analyzing open source information.JRC.E.8-Nuclear securit

Supernarrative country distribution.

The table shows the country distribution of all supernarratives and narratives. The bigger the square, the more articles from the monitored sources of a given country have been assigned to the narrative in question. The colour represents the distribution of articles in percentile across the narrative. Using percentile allows us to display each source country’s ranking within each narrative, despite the different numbers of monitored sources for each country.</p

Evaluation results.

Results of the Precision, Recall and F1 evaluation of BERT classifier on test set.</p

Query. Keyword-based query.

To tackle the COVID-19 infodemic, we analysed 58,625 articles from 460 unverified sources, that is, sources that were indicated by fact checkers and other mis/disinformation experts as frequently spreading mis/disinformation, covering the period from 1 January 2020 to 31 December 2022. Our aim was to identify the main narratives of COVID-19 mis/disinformation, develop a codebook, automate the process of narrative classification by training an automatic classifier, and analyse the spread of narratives over time and across countries. Articles were retrieved with a customised version of the Europe Media Monitor (EMM) processing chain providing a stream of text items. Machine translation was employed to automatically translate non-English text to English and clustering was carried out to group similar articles. A multi-level codebook of COVID-19 mis/disinformation narratives was developed following an inductive approach; a transformer-based model was developed to classify all text items according to the codebook. Using the transformer-based model, we identified 12 supernarratives that evolved over the three years studied. The analysis shows that there are often real events behind mis/disinformation trends, which unverified sources misrepresent or take out of context. We established a process that allows for near real-time monitoring of COVID-19 mis/disinformation. This experience will be useful to analyse mis/disinformation about other topics, such as climate change, migration, and geopolitical developments.</div

Evolution of anti-vax narratives.

The timeline shows the spread over time of “anti-vax narratives,” “anti-mandatory vaccination narratives,” and “anti-vax conspiracy theories”. (TIF)</p