Computational Propaganda Research Articles

Cornered Islamic Society: A Critical Discourse Analysis on Islamophobic Memes

<em>In the era before the internet, memes could take the form of posters containing messages, invitations, and even propaganda. Propagandists manipulated those discourses and presented them at public events such as theatres and festivals. It has evolved into computational propaganda using media and popular memes in the modern era. Muslims are effortless targets for offensive memes, which have been going on for the last decade. This prejudice has become a familiar issue for internet users and vandalizes the image of Muslims and links Muslims to all social problems that transpire in society. This study examined Islamophobic theme memes transmitted on international memetic sites. Popular Islamophobic memes were analyzed using critical discourse analysis to break down the phenomenon based on visual, textual, and social motives. The findings demonstrated that the meme creators utilized the hottest issue to induce the ill idea of demonizing Muslim society and tend to alter the information in their favour. Memes with Islamophobia discourse often included provocative sentences that satirize the teachings of Islam accompanied by words that collocate with aspects of terror, terrorism, radical, extremism, violence, and abuse. That discourse influenced opinions and damaged the image of the target meme, and this method was remarkably efficacious, as evidenced by a large amount of support obtained on anonymous sites. In addition, this meme was distributed in anonymous forums, where this forum ensured the privacy of the meme's sender without worrying that his insults in cyberspace would affect the real world.</em>

Digital Propaganda: The Power of Influencers

Attempts to manipulate public opinion using social media and emerging information communication technologies (ICTs) continue to proliferate internationally. Governments, corporations, extremist groups, and a wide variety of other entities around the globe now commonly use both automated bots and anonymous human "sockpuppet" accounts in efforts to amplify and suppress particular streams of information during elections, security crises, and other pivotal events. They use these same tools to sow disinformation and engage in organized political trolling campaigns. However, the technologies and tactics used in these internet-based "influence operations" are changing. This essay leverages insights from over 70 interviews with people who both produce and track online manipulation campaigns. It compares emerging trends in digital disinformation and computational propaganda across the globe using qualitative data from 12 countries—Burma, Brazil, Egypt, Eritrea, Ethiopia, India, Indonesia, Mexico, the Philippines, Turkey, Ukraine, and the United States. In essence, internet-borne manipulation efforts are evolving from relatively unsophisticated "inorganic" campaigns pushed by social media bots and towards more complex "semi-organic" efforts combining both coordinated human users and artificial intelligence software. Additional, related, trends include the increased coercive political use of social media influencers and encrypted and private messaging applications.

Automated Epistemology: Bots, Computational Propaganda & Information Literacy Instruction

Computational technologies have vastly replaced our prior modalities of information seeking. Social media platforms have become the first choice of many information seekers. Increasingly, these platforms are also becoming vehicles for coordinated, manipulative disinformation campaigns. These campaigns of computational propaganda have resulted in an information environment in which the assignment of authority and trust in information sources has become increasingly opaque. This epistemic process of information evaluation has increasingly become the purview of automated algorithmic systems that we as human beings tend to falsely implicitly trust to provide us with the most accurate information available. Propagandists have begun to exploit the algorithmic components of these systems as well as human cognitive deficits in order to manipulate public opinion, control the narrative of public discourse, and flood our information ecosystems in order to work towards the manufacture of false consensus on a wide range of political and cultural issues. This work aims to review and synthesize the literature on computational propaganda, how it manipulates our human cognitive deficits, and how information literacy can be utilized in order to correct for the resultant epistemic failure.

(Re)shaping online narratives: when bots promote the message of President Trump during his first impeachment.

Influencing and framing debates on Twitter provides power to shape public opinion. Bots have become essential tools of ‘computational propaganda’ on social media such as Twitter, often contributing to a large fraction of the tweets regarding political events such as elections. Although analyses have been conducted regarding the first impeachment of former president Donald Trump, they have been focused on either a manual examination of relatively few tweets to emphasize rhetoric, or the use of Natural Language Processing (NLP) of a much larger corpus with respect to common metrics such as sentiment. In this paper, we complement existing analyses by examining the role of bots in the first impeachment with respect to three questions as follows. (Q1) Are bots actively involved in the debate? (Q2) Do bots target one political affiliation more than another? (Q3) Which sources are used by bots to support their arguments? Our methods start with collecting over 13M tweets on six key dates, from October 6th 2019 to January 21st 2020. We used machine learning to evaluate the sentiment of the tweets (via BERT) and whether it originates from a bot. We then examined these sentiments with respect to a balanced sample of Democrats and Republicans directly relevant to the impeachment, such as House Speaker Nancy Pelosi, senator Mitch McConnell, and (then former Vice President) Joe Biden. The content of posts from bots was further analyzed with respect to the sources used (with bias ratings from AllSides and Ad Fontes) and themes. Our first finding is that bots have played a significant role in contributing to the overall negative tone of the debate (Q1). Bots were targeting Democrats more than Republicans (Q2), as evidenced both by a difference in ratio (bots had more negative-to-positive tweets on Democrats than Republicans) and in composition (use of derogatory nicknames). Finally, the sources provided by bots were almost twice as likely to be from the right than the left, with a noticeable use of hyper-partisan right and most extreme right sources (Q3). Bots were thus purposely used to promote a misleading version of events. Overall, this suggests an intentional use of bots as part of a strategy, thus providing further confirmation that computational propaganda is involved in defining political events in the United States. As any empirical analysis, our work has several limitations. For example, Trump’s rhetoric on Twitter has previously been characterized by an overly negative tone, thus tweets detected as negative may be echoing his message rather than acting against him. Previous works show that this possibility is limited, and its existence would only strengthen our conclusions. As our analysis is based on NLP, we focus on processing a large volume of tweets rather than manually reading all of them, thus future studies may complement our approach by using qualitative methods to assess the specific arguments used by bots.

H-Prop and H-Prop-News: Computational Propaganda Datasets in Hindi

In this digital era, people rely on the internet for their news consumption. As people are free to express their opinions on social media, much information shared on the internet is loaded with propaganda. Propagandist contents are intended to influence public opinion. In the mainstream media or prominent news agencies, the authors’ and news agencies’ own bias may impact in the news contents. Hence, it is required to detect such propaganda spread through news articles. Detection and classification of propagandist text require standard, high-quality, annotated datasets. A few datasets are available for propaganda classification. However, these datasets are mostly in English. Hindi is the most spoken language in India, and efforts are needed to detect its propagandist contents. This research work introduces two new datasets: H-Prop and H-Prop-News, which consist of news articles in Hindi annotated as propaganda or non-propaganda. The H-Prop dataset is generated by translating 28,630 news articles from the QProp dataset. The H-Prop-News dataset contains 5500 news articles collected from 32 prominent Hindi news websites. We experiment with the proposed datasets using four supervised machine learning models combined with different feature vectors and word embeddings. Our experiments achieve 87% accuracy using Logistic Regression with TF-IDF feature vectors. The datasets provide high-quality labeled news articles in Hindi and open new avenues for researchers to explore techniques for analyzing and classifying propaganda in Hindi text.

COMPUTATIONAL PROPAGANDA ON TikTok AS THE 21st CENTURY PROPAGANDA MODEL

Noam Chomsky and Edward Herman wrote an institutional analysis called Propaganda Model that explains the role of mass media in spreading symbols and messages to the general populace under class and power interests requiring systemic propaganda that needs consideration of 5 filters: (1) ownership, (2) advertising, (3) dependence, (4) flak, and anti-communism. Until the emerging of the internet led us to social media features that allow the users to interact socially and artificially. Social media formats are also increasingly diverse and innovative, such as TikTok which was originally released as a music video content platform, and now it’s a place for promotion, information, suggestion, and opinion encouragement content. TikTok content is easily spread across social media because of the ease of download, upload, and access. This study will elaborate on the ease and massiveness of TikTok’s access to the Propaganda Model’s filters to see the current propaganda system mobilization as computational propaganda. The characteristics of computational propaganda are: (1) automation, (2) scalability, (3) anonymity. As a system that makes the public vulnerable to get in the involvement, it’s necessary to form an attitude to deal with it. Therefore, this study offers Noam Chomsky’s idea regarding Intellectual Responsibility as the final contemplation.KEYWORDS: TikTok, computational propaganda, Propaganda Model, intellectual Responsibility.

Misinformation and Fact-checking on the disturbances of the Procés of Catalonia : Digital impact on Public and Media

The outbreak of misinformation and computational propaganda added to the invasion of fake news and the prominence of audiences on social networks becomes a hallmark of the political and media agenda. The publication of the Sentence of the Supreme Court that sanctions the rebellion of independent politicians during the Procés of Catalonia provokes citizen mobilizations that occupy the front pages of the media. The general objective is to know the number and theme of hoaxes spread about the riots on different digital platforms. We apply a content analysis methodology to a general sample (n1=4.500) of hoaxes reported by factchecking agencies (Maldito Bulo, Newtral, Verificat) and news (n2=190) published in the national and international press (El País/el Mundo, El Periódico/Ara, The Guardian/Le Monde). The results confirm that private users are the main authors of fake news and that journalists use verification codes to combat misinformation.

Computational Propaganda in Hashtag Activism

The hashtag (#) has an important role in gathering Internet users' support for opinion and value. Computational propaganda has an important role in hashtag activism. This study wants to examine the role of computational propaganda actors such as anonymous political accounts, fake accounts and bot in social media that is able to mobilize the public and also increase the impression of Twitter audiences. The trend of Twitter hashtag activism #BebaskanIBHRS and #NegaraDamaiTanpaFPI began with the arrest of the chairman of the Islamic Defenders Front (FPI) Habib Rizieq Shihab (HRS); the two trending hashtags massively influenced public opinion on Twitter on December 13-14 2020. This study uses a sample of 1000 tweets or conversations on each hashtags and uses Social Network Analysis (SNA) with the Netlytic tool which is able to provide quantitative values of communication networks, through the social network structure of #BebaskaniBHRS and #NegaraDamaiTanpaFPI. This study reveals how the network structure and what factors are carried out by anonymous political actors in carrying out computational propaganda. The results of this study reveal the hashtags activism #BebaskaniBHRS is much more capable of mobilizing the public and is able to generate greater impressions than #NegaraDamaiTanpaFPI. This is because #BebaskaniBHRS has a computational propaganda message in the form of a loaded language with a clear frame and the choice of words directly invites the Twitter public to get involved through a retweet another finding in this research shows computational propaganda movement in hashtag activism was carried out by large groups consisting of anonymous accounts and bot accounts on other side online media coverage about the trending of these hashtag's activism was also able to increasing public attention. Tagar (#) memiliki peran penting dalam mengumpulkan dukungan pengguna Internet terhadap suatu opini dan nilai. Komputasi propaganda memiliki peran penting dalam aktivisme tagar. Penelitian ini ingin mengkaji peran aktor komputasi propaganda seperti akun anonim politik, akun palsu dan bot di media sosial yang mampu memobilisasi publik dan juga meningkatkan kesan khalayak Twitter. Tren aktivisme tagar Twitter #BebaskanIBHRS dan #NegaraDamaiTanpaFPI dimulai dengan penangkapan ketua Front Pembela Islam (FPI) Habib Rizieq Shihab (HRS); kedua tagar yang sedang trending tersebut secara masif memengaruhi opini publik di Twitter pada 13-14 Desember 2020. Penelitian ini menggunakan sampel 1000 tweet atau percakapan pada masing-masing tagar serta menggunakan Social Network Analysis (SNA) dengan alat Netlytic yang mampu memberikan nilai kuantitatif jaringan komunikasi. Melalui struktur jejaring sosial #BebaskaniBHRS dan #NegaraDamaiTanpaFPI, kajian ini mengungkap seperti apa struktur jaringan komunikasi dan hal apa saja yang dilakukan oleh aktor politik anonim dalam melakukan komputasi propaganda. Hasil penelitian ini mengungkapkan bahwa aktivisme tagar #BebaskaniBHRS jauh lebih mampu memobilisasi publik dan mampu menghasilkan impresi yang lebih besar dibandingkan #NegaraDamaiTanpaFPI. Hal ini dikarenakan #BebaskaniBHRS memiliki pesan komputasi propaganda dalam bentuk bahasa yang sarat dengan bingkai yang jelas dan pilihan kata secara langsung mengajak publik Twitter untuk terlibat melalui retweet.Temuan lain dalam penelitian ini menunjukkan gerakan komputasi propaganda dalam aktivisme tagar dilakukan oleh kelompok besar yang terdiri dari akun anonim dan akun bot di sisi lain liputan media daring tentang tren aktivisme tagar ini juga mampu meningkatkan atensi publik.

Bots as online impersonators

Social bots are automated agents programmed to act on social media impersonating human behaviour to influence discussions online. This paper aims to contribute to the discussion of how bots can endanger online communication and alter information flows. We resorted to a mixed-method approach based on grounded theory and observational techniques in order to investigate the bots’ activities online during the 2016 municipal elections in Rio de Janeiro. We collected related content on Twitter in this period and detected 3,101 bots. This sample was classified in three categories based on tweeting content: user-generated bot, media spambot, and political bot. Our findings indicate that, although bots work for different political and social purposes, their computational nature claims into service of dominant social groups and economical elites. We conclude that computational propaganda is building a dangerous scenario of widespread automation in which different kinds of algorithms bias social media conversation.

The Connotation, Features, and Mechanism of Computational Propaganda

The purpose of the work is to identify the connotation, features of computational propaganda and reveal how computational propaganda uses new technologies to manipulate public opinion.
 The study’s hypothesis is the assumption that computational propaganda, as a new type of propaganda and manipulation of public opinion spawned in the era of artificial intelligence, stealthily and massively steers public opinion using new technologies to influence political and social processes.
 With the scientific methods such as event analysis and case-study, the work concludes that more and more governments, political parties, and strategic communication companies use social media as the digital platform, Internet bots as the automated executors, and algorithms as the computational technical guarantee, by participating in, guiding and creating controversial topics and events, to manipulate public opinion and win international competitions, policy debates, elections, etc.

Tricked into Supporting: A Study on Computational Propaganda Persuasion Strategies

The study reported in this paper aims to theoretically and empirically explore computational propaganda (CP) – a systematic process of political misinformation perpetrated on social networking platforms by automated agents with the aim of increasing support for specific political stances – focusing in particular on the factors determining its potential effectiveness. The claim maintained throughout this paper is that, among the possible factors determining this effectiveness, a pivotal one is represented by the design of CP messages themselves. Indeed, the hypothesis underlying this investigation is that the way CP content is created and presented is not casual, but deliberately designed to embed in it a set of persuasion strategies aimed at triggering a specific cognitive deliberation: considering misinformation as factual. Drawing from the Dual Process Theory of Cognition, the argument proposed is that info-cues contained in CP messages play a pivotal role in determining the likelihood of CP effectiveness. To test this hypothesis, a two-step analysis characterized by a mixed-method strategy has been implemented. To identify and collect CP messages, a machine learning algorithm able to perform bot-detection has been developed, while to analyze the content of those messages, a combination of qualitative and quantitative text analysis techniques has been employed. Lastly, preliminary results are presented and future work discussed.

Towards an Online Risk Mitigation Framework for Political Brands Subject to Computational Propaganda

The influence of computational propaganda on democratic processes globally has necessitated the exploration of mitigation strategies for political brands. The risk associated with computational propaganda includes the spread of misleading information about a political brand over social networking sites through bots (i.e. automated software applications that are programmed to do certain tasks) and newsfeed algorithms at rapid speeds. Apart from bots being used to facilitate the spread of disinformation (i.e. misleading information spread with the intent to manipulate or deceive), human curators also play a role. Research into addressing computational propaganda in the field of political communication is limited, compelling the need to look to consumer brand experts for insight. The current study used semi-structured interviews of senior consumer brand social media practitioners and applied content analysis to develop a framework for mitigating online brand risk associated with computational propaganda for political brands. This computational propaganda brand risk mitigation framework proposes two approaches to curb the effects of computational propaganda, namely, a preventative approach and a recovery approach. Based on established theoretical and practical concepts, this mitigation framework could guide the easing of online brand risk and associated crises for political brands.

Political Communication in Computational Propaganda: 23 June 2019 Istanbul Local Elections and Bots, Cyborgs, Trolls in Turkey

Sosyal medya kullanımının ayrılmaz parçaları olan trol, bot ve cyborg gibi araçlar, bilişimsel propaganda etkileriyle demokrasiyi tehdit etmeye başlamışlardır. Bu nedenle, Türkiye’de sosyal medya üzerinden yapılan iletişimde bu unsurların kullanıp kullanılmadığı, kullanıldıysa hangi oranda kullanıldığının bulunması önemli bir meseledir ve araştırmaya değerdir. 23 Haziran 2019 Seçimleri, böylesi bir araştırma için iyi bir ortam sunmaktadır. Bu araştırmada Türkiye’de Twitter trafiği içerisinde trol, bot ve cyborg hesapları konu edinilmiştir. 2019 Haziran İstanbul Büyükşehir Belediye Başkanlığı seçimlerinde aday olan Binali Yıldırım ve Ekrem İmamoğlu’nun Twitter seçim kampanyalarını yürüttükleri hesapların takipçilerine, iletilerine etkileşimli olarak katılan ve katkı sağlayan hesaplara odaklanılmıştır. Bu araştırmanın amacı, Türkiye’de Twitter trafiği içerisinde trol hesaplarının yanı sıra bot ve cyborg hesaplarının yaygın olup olmadığını belirlemesidir. Adayların hashtagler’inin diğer kullanıcılarca hangi kaynaklardan dolaşıma sokulduğu GitHub TCAT açık kaynak yazılımıyla gerçekleşmiştir. Bot ya da cyborg şüphelisi hesaplara rastlanmış; en aktif ikişer tanesi ağ analizi ve görselleştirme yazılımı olan Gephi ile takibe alınmıştır. Araştırma sonucunda cyborg ve bot gibi otomatikleşmiş hesaplara rastlanmış; bu türden hesapların yalnızca siyasetçilerin takipçi kullanıcıları tarafından değil, kamu gündemi yaratmaya çalışan çıkar grupları tarafından da kullanılmaya başlandığı sonucuna ulaşılmıştır.

Социальные боты в компьютерной пропаганде: серфинг на информационной волне коронавируса

В статье современный феномен инфодемии рассматривается как расширение латентных механизмов информационного воздействия. Авторы интерпретируют этот процесс в контексте концепта компьютерной пропаганды, который позволяет не только описать использование новых компьютерных технологий для манипуляции и дезинформации в социальных сетях (конструирования фейковой информации, функционирования социальных ботов и др.), но и выявить скрытые цели субъектов пропаганды в современном онлайн-пространстве. Исследовательская цель статьи связана с анализом использования социальных ботов для пропагандистского воздействия, осуществляемого на информационной волне коронавирусной эпидемической ситуации. Для реализации поставленной цели были решены следующие задачи: 1) осуществлен аналитический обзор источников, где описаны новые формы и способы дезинформации в различных социальных сетях, возникшие на волне коронавирусной инфодемии — фейковых новостей, социальных ботов; 2) представлены результаты пилотажного исследования по выявлению и описанию бот-сетей в процессе тематического мониторинга социальной сети «ВКонтакте», связанных с тематикой коронавируса и функционирование которых может быть интерпретировано в контексте компьютерной пропаганды. Исследование проводилось на базе Центра социологических и интернет-исследований СПбГУ в период с 16 марта по 26 мая 2020 г. по авторской методике анализа всплесков сетевой публикационной активности в сочетании с комплексной методикой выявления ботнетов, включающей метод частотного анализа размещаемых сообщений, профайлинг бот-аккаунтов, статистический анализ текстов, анализ структурной организации бот-сети, а также анализ контента публикаций. В результате был обнаружен ряд ботнетов, которые, используя волну популярной темы коронавируса в пропагандистских целях, осуществляют продвижение в информационном поле социальной сети: 1) оппозиционного политического контента с критикой власти и отечественной системы здравоохранения; 2) конспирологических нарративов, связанных с опасностью массового отравления продуктов, воды и лекарственных препаратов, а также с опасностью «цифрового рабства» населения путем массового введения биометрических данных. Благодарность. Исследование выполнено в рамках гранта РФФИ 20-011-31318 «Коммуникативные стратегии политико-ориентированных онлайн-сообществ в социальных сетях». Исследование проведено с использованием оборудования Центра социологических и интернет-исследований Санкт-Петербургского государственного университета.

컴퓨테이셔널 프로파간다에 대한 탐색적 시론 : 정치적 봇과 그 사회정치적 의미를 중심으로

이 글은 컴퓨테이셔널 프로파간다 현상에 관한 탐색적 시론이다. 그간 국내 언론학에서 이에 관한 이슈는 주로 가짜뉴스 또는 허위조작정보의 맥락 안에서 검토된 반면, 디지털 환경에서의 정치 커뮤니케이션이라는 맥락에서 살펴본 논의는 많지 않다. 연구진은 컴퓨테이셔널 프로파간다의 개념화, 사례들 그리고 규범적 대응 방안에 관한 그간의 논의를 비판적으로 재검토하고 기술과 인간 행위자의 연속체라는 관점에서 이 관행에 대해 소개한다. 앞으로의 정치 커뮤니케이션에서 컴퓨테이셔널한 커뮤니케이션 관행은 더욱 일상화되고 보편화될 것으로 예측되는 상황에서 컴퓨테이셔널 프로파간다와 전통 프로파간다 사이의 연속성과 불연속성에 대한 포괄적 이해가 필요하다. 이 연구를 통해 봇과 같은 비ᐨ인간 요소들과 결합된 새로운 프로파간다 관행과 그 의미에 대한 학계의 관심과 공동체 차원의 논의가 진전되기를 기대한다.

Prediction of Social Influence for Provenance of Misinformation in Online Social Network Using Big Data Approach

AbstractOnline social networks (OSNs) is a platform that plays an essential role in identifying misinformation like false rumors, insults, pranks, hoaxes, spear phishing and computational propaganda in a better way. Detection of misinformation finds its applications in areas such as law enforcement to pinpoint culprits who spread rumors to harm the society, targeted marketing in e-commerce to identify the user who originates dissatisfaction messages about products or services that harm an organizations reputation. The process of identifying and detecting misinformation is very crucial in complex social networks. As misinformation in social network is identified by designing and placing the monitors, computing the minimum number of monitors for detecting misinformation is a very trivial work in the complex social network. The proposed approach determines the top suspected sources of misinformation using a tweet polarity-based ranking system in tandem with sarcasm detection (both implicit and explicit sarcasm) with optimization approaches on large-scale incomplete network. The algorithm subsequently uses this determined feature to place the minimum set of monitors in the network for detecting misinformation. The proposed work focuses on the timely detection of misinformation by limiting the distance between the suspected sources and the monitors. The proposed work also determines the root cause of misinformation (provenance) by using a combination of network-based and content-based approaches. The proposed work is compared with the state-of-art work and has observed that the proposed algorithm produces better results than existing methods.

Political communication in post-truth society

The research behind this paper is set in the context of the 2016 US presidential election that has come to symbolize the post-truth era. We conducted a literature review on the 2016 election, with the aim to better understand the impact of computational propaganda on the election outcome and on the behaviour of voters. The paper opens with a definition of post-truth society and related concepts such as fake news and computational propaganda. It explores the changes of political communication in a digital environment and analyses the role of social media in the 2016 election. It probes into phenomena such as the trivialization of politics and the loss of credibility of political actors, which are both common in post-truth societies. The reviewed literature seems to indicate that social media have become strong actors on the political stage, but so far not the predominant source of political information and influence on the behaviour of voters. The paper makes two important contributions. Firstly, drawing on the concept of post-truth society, it analyses the role of computational propaganda in the 2016 presidential election, and secondly, it attempts to explain the paradox of general political apathy on one hand, and increased political activism on the other. These are some of the challenges we are now facing, and in order to be able to cope with them it is important to acknowledge and understand them.

Computational propaganda: political parties, politicians, and political manipulation on social media

Computational propaganda: political parties, politicians, and political manipulation on social media

The clash of empires: regulating technological threats to civil society

ABSTRACTThis paper examines the regulation of technology platform companies providing a platform for user-generated media content while playing an increasingly dominant role in the global flow of news and information. In doing so, platform companies play a crucial role in modern civic life, by deciding which content will reach users, engage the public's attention, and be deemed credible. It is therefore crucial that we choose means of regulation that foster democratic values and robust civic engagement. In this paper we focus on the regulation of ‘computational propaganda', including misinformation and ‘fake news', the rise of synthetic media and so-called ‘deep fakes', and novel forms of algorithmic injustice, such as the manipulation of search engine results and their effect on elections. We argue that many existing regulations fall short in that they adopt an approach that views regulation as a battle between two competing powers, or ‘empires’ – that of the regulatory state versus the big tech companies. Accordingly, they approach regulation as a means of redistributing power between these two players, while discounting the end user, and they often involve unjustified restrictions of free speech through the imposition of content controls.

GOVERNANCE OF THE FACEBOOK PRIVACY CRISIS

In November 2018, The New York Times ran a front-page story describing how Facebook concealed knowledge and disclosure of Russian-linked activity and exploitation resulting in Kremlin led disruption of the 2016 and 2018 U.S. elections, through the use of global hate campaigns and propaganda warfare. By mid-December 2018, it became clear that the Russian efforts leading up to the 2016 U.S. elections were much more extensive than previously thought. Two studies conducted for the United States Senate Select Committee on Intelligence (SSCI), by: (1) Oxford University’s Computational Propaganda Project and Graphika; and (2) New Knowledge, provide considerable new information and analysis about the Russian Internet Research Agency (IRA) influence operations targeting American citizens.By early 2019 it became apparent that a number of influential and successful high growth social media platforms had been used by nation states for propaganda purposes. Over two years earlier, Russia was called out by the U.S. intelligence community for their meddling with the 2016 American presidential elections. The extent to which prominent social media platforms have been used, either willingly or without their knowledge, by foreign powers continues to be investigated as this Article goes to press. Reporting by The New York Times suggests that it wasn’t until the Facebook board meeting held September 6, 2017 that board audit committee chairman, Erskin Bowles, became aware of Facebook’s internal awareness of the extent to which Russian operatives had utilized the Facebook and Instagram platforms for influence campaigns in the United States. As this Article goes to press, the degree to which the allure of advertising revenues blinded Facebook to their complicit role in offering the highest bidder access to Facebook users is not yet fully known. This Article can not be a complete chapter in the corporate governance challenge of managing, monitoring, and oversight of individual privacy issues and content integrity on prominent social media platforms. The full extent of Facebook’s experience is just now becoming known, with new revelations yet to come. All interested parties: Facebook users; shareholders; the board of directors at Facebook; government regulatory agencies such as the Federal Trade Commission (FTC) and Securities and Exchange Commission (SEC); and Congress must now figure out what has transpired and what to do about it. These and other revelations have resulted in a crisis for Facebook. American democracy has been and continues to be under attack. This article contributes to the literature by providing background and an account of what is known to date and posits recommendations for corrective action.