Query: disinformation

title: Technological Approaches to Detecting Online Disinformation and Manipulation
abstract: The move of propaganda and disinformation to the online environment is possible thanks to the fact that within the last decade, digital information channels radically increased in popularity as a news source. The main advantage of such media lies in the speed of information creation and dissemination. This, on the other hand, inevitably adds pressure, accelerating editorial work, fact checking, and the scrutiny of source credibility. In this chapter, an overview of computer supported approaches to detecting disinformation and manipulative techniques based on several criteria is presented. We concentrate on the technical aspects of automatic methods which support fact checking, topic identification, text style analysis, or message filtering on social media channels. Most of the techniques employ artificial intelligence and machine learning with feature extraction combining available information resources. The following text firstly specifies the tasks related to computer detection of manipulation and disinformation spreading. The second section presents concrete methods of solving the tasks of the analysis, and the third sections enlists current verification and benchmarking datasets published and used in this area for evaluation and comparison.

title: Inoculating against the spread of Islamophobic and radical Islamist disinformation
abstract: We report the results of a preregistered study that tested the effectiveness of inoculating participants against Islamophobic and radical Islamist disinformation. Participants in the experimental (inoculation) condition watched a video that explained common rhetorical markers of radical Islamist and Islamophobic disinformation that had been identified in an analysis of YouTube content. The information was presented in a neutral context not involving Islam and focused on analysis of the misleading argumentation. The control group watched a video about an unrelated topic. Participants were then exposed to target videos with "gateway" content that constituted an entry point to potential Islamist or Islamophobic radicalization. Both videos contained numerous items of disinformation. Participants then answered a variety of questions such as how likely they were to share the video, their level of agreement, and their perceived accuracy of the video. Participants who had received the inoculation displayed less agreement with the video content, perceived the video as less reliable, and were less likely to share it in comparison with participants in the control group. The study provides support for the use of argument based inoculation in combatting extremist messages.

title: Fake News, Disinformation, Propaganda, Media Bias, and Flattening the Curve of the COVID 19 Infodemic
abstract: The rise of social media has democratized content creation and has made it easy for anybody to share and to spread information online. On the positive side, this has given rise to citizen journalism, thus enabling much faster dissemination of information compared to what was possible with newspapers, radio, and TV. On the negative side, stripping traditional media from their gate keeping role has left the public unprotected against the spread of disinformation, which could now travel at breaking news speed over the same democratic channel. This situation gave rise to the proliferation of false information, specifically created to affect individual people's beliefs, and ultimately to influence major events such as political elections; it also set the dawn of the Post Truth Era, where appeal to emotions has become more important than the truth. More recently, with the emergence of the COVID 19 pandemic, a new blending of medical and political misinformation and disinformation has given rise to the first global infodemic. Limiting the impact of these negative developments has become a major focus for journalists, social media companies, and regulatory authorities. We offer an overview of the emerging and inter connected research areas of fact checking, misinformation, disinformation, "fake news' propaganda, and media bias detection, with focus on text and computational approaches. We explore the general fact checking pipeline and important elements thereof such as check worthiness estimation, spotting previously fact checked claims, stance detection, source reliability estimation, detection of persuasion/propaganda techniques in text and memes, and detecting malicious users in social media. We further cover large scale pre trained language models, and the challenges and opportunities they offer for generating and for defending against neural fake news. Finally, we explore some recent efforts towards flattening the curve of the COVID 19 infodemic.

title: Deriving Disinformation Insights from Geolocalized Twitter Callouts
abstract: This paper demonstrates a two stage method for deriving insights from social media data relating to disinformation by applying a combination of geospatial classification and embedding based language modelling across multiple languages. In particular, the analysis in centered on Twitter and disinformation for three European languages: English, French and Spanish. Firstly, Twitter data is classified into European and non European sets using BERT. Secondly, Word2vec is applied to the classified texts resulting in Eurocentric, non Eurocentric and global representations of the data for the three target languages. This comparative analysis demonstrates not only the efficacy of the classification method but also highlights geographic, temporal and linguistic differences in the disinformationrelated media. Thus, the contributions of the work are threefold: (i) a novel language independent transformer based geolocation method; (ii) an analytical approach that exploits lexical specificity and word embeddings to interrogate user generated content; and (iii) a dataset of 36 million disinformation related tweets in English, French and Spanish.

title: Is it Fake? News Disinformation Detection on South African News Websites
abstract: Disinformation through fake news is an ongoing problem in our society and has become easily spread through social media. The most costand time effective way to filter these large amounts of data is to use a combination of human and technical interventions to identify it. From a technical perspective, Natural Language Processing (NLP) is widely used in detecting fake news. Social media companies use NLP techniques to identify the fake news and warn their users, but fake news may still slip through undetected. It is especially a problem in more localised contexts (outside the United States of America) How do we adjust fake news detection systems to work better for local contexts such as in South Africa. In this work we investigate fake news detection on South African websites. We curate a dataset of South African fake news and then train detection models. We contrast this with using widely available fake news datasets (from mostly USA website) We also explore making the datasets more diverse by combining them and observe the differences in behaviour in writing between nations' fake news using interpretable machine learning.

title: Novel technologies and Geopolitical Strategies: Disinformation Narratives in the Countries of the Visegrad Group
abstract: In the current media environment of growing information disorder and social media platforms emerging as primary news sources, the creation and spread of disinformation is becoming increasingly easy and cost effective. The projection of strategic narratives through disinformation campaigns is an important geopolitical tool in the global competition for power and status. We have analysed close to 1,000 individual news pieces from more than 60 different online sources containing disinformation, which originally appeared in one of the V4 languages, using a natural language processing algorithm. We have assessed the frequency of recurring themes within the articles and their relationship structure, to see whether consistent disinformation narratives were to be found among them. Through frequency analysis and relationship charting, we have been able to uncover individual storylines connected to more than ten overarching disinformation narratives. We have also exposed five key meta narratives present in all Visegrad Countries, which fed into a coherent system of beliefs, such as the envisioned collapse of the European Union or the establishment of a system of Neo Atlantism, which would permanently divide the continent.

title: Characterizing Online Engagement with Disinformation and Conspiracies in the 2020 U.S. Presidential Election
abstract: Identifying and characterizing disinformation in political discourse on social media is critical to ensure the integrity of elections and democratic processes around the world. Persistent manipulation of social media has resulted in increased concerns regarding the 2020 U.S. Presidential Election, due to its potential to influence individual opinions and social dynamics. In this work, we focus on the identification of distorted facts, in the form of unreliable and conspiratorial narratives in election related tweets, to characterize discourse manipulation prior to the election. We apply a detection model to separate factual from unreliable (or conspiratorial) claims analyzing a dataset of 242 million election related tweets. The identified claims are used to investigate targeted topics of disinformation, and conspiracy groups, most notably the far right QAnon conspiracy group. Further, we characterize account engagements with unreliable and conspiracy tweets, and with the QAnon conspiracy group, by political leaning and tweet types. Finally, using a regression discontinuity design, we investigate whether Twitter's actions to curb QAnon activity on the platform were effective, and how QAnon accounts adapt to Twitter's restrictions.

title: Book Review: Digital Democracy, Social Media and Disinformation by Petros Iosifidis and Nicholas Nicoli
abstract: In the spheres of political communication and digital media, there are few more pressing issues than disinformation and misinformation. The need to ensure freedom of speech and expression while also legislating against and eliminating disinformation and hateful speech has become one of democracy's most imperative tasks. This is an ideal which has recently been thrown into disarray by the conjunction of technological enhancements and politico economic actors with divisive, authoritarian agendas. Iosifidis and Nicoli's concise and timely volume is suffused by a sense of urgency at the ways in which digital disinformation is eroding democracy, trust, and informed participation, even in countries that they argue to have been historically aligned with enlightenment ideals and liberal political traditions. Nor are the only dangers to democracy from state and nonstate actors who are explicitly using the internet to spread disinformation and fake news. After mentioning the generally accepted positives of the internet for activism and democratic participation, their opening sections question what citizens choose to do online in "selectively exposing the issues that matter to them individually rather than to society as a whole" (p. 23) Confirmation bias and targeted psychographic profiling by firms to whom platforms have sold personal data are only the beginning when it comes to the dangers highlighted. The opening literature review situates the Habermassian public sphere as an ideal to which the authors are committed, despite the critiques that they briefly reflect on. And indeed, seen from the perspective of this ideal of political civility rational, representative, dominated by neither state nor market and working towards the public good for the greatest number through reconciliation of values and a maximization of wellbeing our current political and media systems and the debates that we find ourselves in on social media platforms seem hopelessly compromized and inadequate. The discussion of scholarship with regard to citizenship and public spheres is balanced, taking neither a techno optimist nor an overly techno pessimist view, if rather limited both by its citation of mainly well regarded European and American literature Book Review

title: The Impact of Disinformation on a Controversial Debate on Social Media
abstract: In this work we study how pervasive is the presence of disinformation in the Italian debate around immigration on Twitter and the role of automated accounts in the diffusion of such content. By characterising the Twitter users with an Untrustworthiness score, that tells us how frequently they engage with disinformation content, we are able to see that such bad information consumption habits are not equally distributed across the users; adopting a network analysis approach, we can identify communities characterised by a very high presence of users that frequently share content from unreliable news sources. Within this context, social bots tend to inject in the network more malicious content, that often remains confined in a limited number of clusters; instead, they target reliable content in order to diversify their reach. The evidence we gather suggests that, at least in this particular case study, there is a strong interplay between social bots and users engaging with unreliable content, influencing the diffusion of the latter across the network.

title: A Comparative Study of Online Disinformation and Offline Protests
abstract: In early 2021 the United States Capitol in Washington was stormed during a riot and violent attack. Although the storming was merely an instance in a long sequence of events, it provided a testimony for many observers who had claimed that online actions, including the propagation of disinformation, have offline consequences. Soon after, a number of papers have been published about the relation between online disinformation and offline violence, among other related relations. Hitherto, the effects upon political protests have been unexplored. This paper thus evaluates such effects with a time series cross sectional sample of 125 countries in a period between 2000 and 2019. The results are mixed. Based on Bayesian multi level regression modeling, (i) there indeed is an effect between online disinformation and offline protests, but the effect is partially meditated by political polarization. The results are clearer in a sample of countries belonging to the European Economic Area. With this sample, (ii) offline protest counts increase from online disinformation disseminated by domestic governments, political parties, and politicians as well as by foreign governments. Furthermore, (iii) Internet shutdowns and governmental monitoring of social media tend to decrease the counts. With these results, the paper contributes to the blossoming disinformation research by modeling the impact of disinformation upon offline phenomenon. The contribution is important due to the various policy measures planned or already enacted.