User Guidance for Efficient Fact Checking

The Web constitutes a valuable source of information. In recent years, it fostered the construction of large-scale knowledge bases, such as Freebase, YAGO, and DBpedia. The open nature of the Web, with content potentially being generated by everyone, however, leads to inaccuracies and misinformation. Construction and maintenance of a knowledge base thus has to rely on fact checking, an assessment of the credibility of facts. Due to an inherent lack of ground truth information, such fact checking cannot be done in a purely automated manner, but requires human involvement. In this paper, we propose a comprehensive framework to guide users in the validation of facts, striving for a minimisation of the invested effort. Our framework is grounded in a novel probabilistic model that combines user input with automated credibility inference. Based thereon, we show how to guide users in fact checking by identifying the facts for which validation is most beneficial. Moreover, our framework includes techniques to reduce the manual effort invested in fact checking by determining when to stop the validation and by supporting efficient batching strategies. We further show how to handle fact checking in a streaming setting. Our experiments with three real-world datasets demonstrate the efficiency and effectiveness of our framework: A knowledge base of high quality, with a precision of above 90\%, is constructed with only a half of the validation effort required by baseline techniques

Artificial intelligence in journalism: Automatic translation and recommendation system in the project “A European Perspective

On July 1st, 2021, several European public broadcasters officially launched the project “A European Perspective”. It is an online news exchange service developed within the EBU European Broadcasting Union, which brought together ten public broadcast companies from nine countries. This project uses Artificial Intelligence for the translation and recommendation of content produced by the participants and that can be freely used on their websites. The main objectives of the project are the fight against misinformation and the affirmation of the European values in a social context in which social networks have been gaining more and more influence among public opinion. Methodology: This paper, a case study, explains how the project works and analyses the type of content shared in the first two months of operation on the website of RTP-Rádio Televisão Portuguesa

Artificial intelligence in journalism: Automatic translation and recommendation system in the project “A European Perspective” (EBU)

Introducción: El 1 de julio de 2021, varios organismos públicos de radiodifusión europeos lanzaron oficialmente el proyecto “A European Perspective”. Se trata de un servicio de intercambio de noticias en línea desarrollado dentro del ámbito de la UER - Unión Europea de Radiodifusión, que reunió a diez empresas de radio y televisión públicas de nueve países. Este proyecto utiliza la Inteligencia Artificial para la traducción y recomendación de contenidos producidos por los participantes y que pueden ser utilizados libremente en sus sitios web. Entre los objetivos del proyecto se encuentran la lucha contra la desinformación y la afirmación de los valores europeos en un contexto social en el que las redes sociales han ido ganando cada vez más influencia entre la opinión pública. Metodología: Este trabajo es un estudio de caso y, además de explicar cómo funciona el proyecto, hace un análisis de los contenidos compartidos en los dos primeros meses de funcionamiento en el sitio web de la televisión pública portuguesa RTP- Rádio Televisão Portuguesa. Resultados y Conclusiones: El proyecto está cumpliendo los objetivos inicialmente definidos por la UER, especialmente en cuanto a ofrecer diferentes perspectivas sobre temas que son objeto de procesos de desinformación, como la pandemia, y solidificando una visión europea basada en el rigor y la transparencia de la información producida por los operadores de radio y televisión pública.Introduction: On July 1st, 2021, several European public broadcasters officially launched the project “A European Perspective”. It is an online news exchange service developed within the EBU - European Broadcasting Union, which brought together ten public broadcast companies from nine countries. This project uses Artificial Intelligence for the translation and recommendation of content produced by the participants and that can be freely used on their websites. The main objectives of the project are the fight against misinformation and the affirmation of the European values in a social context in which social networks have been gaining more and more influence among public opinion. Methodology: This paper, a case study, explains how the project works and analyses the type of content shared in the first two months of operation on the website of RTP- Rádio Televisão Portuguesa. Results and Conclusions The project is meeting the objectives initially defined by the EBU, especially in terms of offering different perspectives on issues that are subject to disinformation processes, such as the pandemic, and solidifying a European vision based on rigor and transparency of the news produced by public European broadcasters.info:eu-repo/semantics/publishedVersio

Graph-based Rumour Detection for Social Media

Social platforms became a major source of rumours. While rumours can have severe real-world implications, their detection is notoriously hard: Content on social platforms is short and lacks semantics; it spreads quickly through a dynamically evolving network; and without considering the context of content, it may be impossible to arrive at a truthful interpretation. Traditional approaches to rumour detection, however, exploit solely a single content modality, e.g., social media posts, which limits their detection accuracy. In this paper, we cope with the aforementioned challenges by means of a multi-modal approach to rumour detection that identifies anomalies in both, the entities (e.g., users, posts, and hashtags) of a social platform and their relations. Based on local anomalies, we show how to detect rumours at the network level, following a graph-based scan approach

Η πανδημία και τα fake news περί αυτής. Το φαινόμενο σε Ελλάδα, Ευρώπη και ΗΠΑ.

Η παρούσα εργασία ασχολείται με το φαινόμενο των ψευδών ειδήσεων (fake news), τόσο στην Ελλάδα όσο και σε άλλες ευρωπαϊκές χώρες αλλά και στις ΗΠΑ, όπου μέσω της ανάλυση ερευνών κοινής γνώμης θα προσπαθήσουμε να διαπιστώσουμε το εύρος της επιρροής των ψευδών ειδήσεων κατά του κορονοϊού και κατά πόσο επηρέασαν τις εμβολιαστικές εκστρατείες για τον COVID-19 και να σκιαγραφήσουμε το προφίλ των ατόμων που ανήκουν στο λεγόμενο «αντιεμβολιαστικό κίνημα».This paper studies the impact of fake news on the vaccination campaigns during the covid-19 pandemic as well as the impact of the fake news phenomenon in the "fight" against the new corona virus

Quem consome Fake News? Uma análise comparativa do efeito da ideologia política Esquerda-Direita na crença, interpretação e divulgação

A criação e a disseminação de conteúdos falsos, como ações de instrumentalização política, sempre fez parte dos jogos de manipulação e das manobras políticas inerentes à sociedade humana. No entanto, atualmente, com um mundo cada vez mais digital, sem limitações geográficas que impeçam as pessoas de estar constantemente interligadas e conectadas, a desinformação pode ser disseminada de forma massiva e a uma velocidade sem precedentes, ameaçando os fundamentos basilares do jornalismo e as demais instituições democráticas. Numa época em que existe um profundo desprezo pela verdade e pela evidência científica, na qual a credibilidade e a confiança nas principais instituições públicas e políticas, estão em crise, a mentira, sob o disfarce de notícias legítimas, compete, no mesmo ambiente digital, com os meios de comunicação pela atenção de uma audiência cada vez mais fragmentada, polarizada e seletiva. Depois das eleições presidenciais americanas de 2016, a criação de fake news passou a ser uma arma política frequentemente utilizada por agentes estatais e/ou independentes, com o objetivo de obterem, essencialmente, ganhos políticos, desacreditando adversários e manipulando eleitores em períodos de campanha eleitoral. À semelhança de outros países ocidentais, também em Portugal a disseminação de fake news políticas através das redes sociais, procura destabilizar a vida pública e política da sociedade. Considerando este contexto, este trabalho visa analisar a suscetibilidade dos eleitores portugueses a fake news contemporâneas, politicamente enviesadas. A nossa investigação procura, deste modo, compreender a influência das identidades ideológicas e partidárias na crença e divulgação de fake news e notícias politicamente comprometedoras, em conformidade com diferentes estilos cognitivos de processar informação e diferentes práticas de consumir informação online. Interessa, desta forma, identificar possíveis assimetrias ideológicas (esquerda vs direita), cognitivas e partidárias no que diz respeito ao consumo e disseminação de fake news políticas, ao mesmo tempo que se realiza uma auscultação geral da vulnerabilidade do eleitorado português, quando exposto a este tipo de conteúdos. Desta forma, propondo a apresentação de um inquérito por questionário, foi desenvolvida uma metodologia capaz de conciliar diferentes instrumentos e procedimentos para identificar ideológica e partidariamente os participantes, avaliando a sua habilidade cognitiva e as suas práticas de consumir informação online. A par destes métodos, os participantes foram convidados a avaliar a credibilidade e a manifestar a intenção de partilhar um conjunto de títulos de fake news e notícias. Este estudo pretende ser um contributo relevante para a investigação nesta área, sobretudo em Portugal. Acreditamos que este trabalho possa ser enriquecedor para a literatura, nomeadamente no que diz respeito à conceção de uma estrutura validada para a medição da suscetibilidade à desinformação.The creation and dissemination of false content, such as political instrumentalization actions, has always been part of the manipulation games and political maneuvers inherent to human society. However, currently, with an increasingly digital world, without geographic limitations that prevent people from being constantly connected, disinformation can be disseminated massively and at breakneck speed, threatening the basic pillars of journalism and other democratic institutions. At a time when there is a profound contempt for truth and scientific evidence, in which the credibility and trust of the main public and political institutions is in crisis, the lie, under the guise of legitimate news, competes, in the same digital environment, with the media for the attention of an increasingly fragmented, polarized and selective audience. After the 2016 US presidential elections, the creation of fake news became a political weapon frequently used by the state and/or independent agents, with the objective of essentially obtaining political gains, discrediting political opponents and manipulating voters in electoral campaign periods. As in other western countries, in Portugal, the dissemination of political fake news, through digital social networks, seeks to destabilize society's public and political life. Considering this context, this work aims to analyze the susceptibility to contemporary, politically biased fake news. In this way, our research seeks to understand the influence of ideological and party identities on the belief and dissemination of fake news and politically compromising news, in accordance with different cognitive styles of processing information and different practices of consuming information online. It is therefore interesting to identify possible ideological (left vs. right), cognitive and partisan asymmetries with regard to the consumption and dissemination of political fake news, while at the same time conducting a general survey of the vulnerability of the Portuguese electorate, when exposed to this kind of content. Thus, proposing the presentation of an inquiry by questionnaire, we developed a methodology capable of reconciling different instruments and procedures to identify participants ideologically and in a party way, evaluating their cognitive ability and their practices when consuming information online. Alongside these methods, participants were invited to assess the credibility and express their intention to share a set of fake news and news headlines. This study intends to be a relevant contribution to research in this area, especially in Portugal. We believe that this work can be enriching for the literature, namely with regard to the design of a validated structure for measuring the susceptibility to disinformation

User guidance for efficient fact checking

The Web constitutes a valuable source of information. In recent years, it fostered the construction of large-scale knowledge bases, such as Freebase, YAGO, and DBpedia. The open nature of the Web, with content potentially being generated by everyone, however, leads to inaccuracies and misinformation. Construction and maintenance of a knowledge base thus has to rely on fact checking, an assessment of the credibility of facts. Due to an inherent lack of ground truth information, such fact checking cannot be done in a purely automated manner, but requires human involvement. In this paper, we propose a comprehensive framework to guide users in the validation of facts, striving for a minimisation of the invested effort. Our framework is grounded in a novel probabilistic model that combines user input with automated credibility inference. Based thereon, we show how to guide users in fact checking by identifying the facts for which validation is most beneficial. Moreover, our framework includes techniques to reduce the manual effort invested in fact checking by determining when to stop the validation and by supporting efficient batching strategies. We further show how to handle fact checking in a streaming setting. Our experiments with three real-world datasets demonstrate the efficiency and effectiveness of our framework: A knowledge base of high quality, with a precision of above 90%, is constructed with only a half of the validation effort required by baseline techniques