Introduction: What Is Computational Propaganda?
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Arxiv:1805.10105V1 [Cs.SI] 25 May 2018
Effects of Social Bots in the Iran-Debate on Twitter Andree Thieltges, Orestis Papakyriakopoulos, Juan Carlos Medina Serrano, Simon Hegelich Bavarian School of Public Policy Technical University of Munich Abstract Ahmadinejad caused nationwide unrests and protests. As these protests grew, the Iranian government shut down for- 2018 started with massive protests in Iran, bringing back the eign news coverage and restricted the use of cell phones, impressions of the so called “Arab Spring” and it’s revolution- text-messaging and internet access. Nevertheless, Twitter ary impact for the Maghreb states, Syria and Egypt. Many reports and scientific examinations considered online social and Facebook “became vital tools to relay news and infor- mation on anti-government protest to the people inside and networks (OSN’s) such as Twitter or Facebook to play a criti- 1 cal role in the opinion making of people behind those protests. outside Iran” . While Ayatollah Khameini characterized the Beside that, there is also evidence for directed manipulation influence of Twitter as “deviant” and inappropriate on Ira- of opinion with the help of social bots and fake accounts. nian domestic affairs2, most of the foreign news coverage So, it is obvious to ask, if there is an attempt to manipulate hailed Twitter to be “a new and influential medium for social the opinion-making process related to the Iranian protest in movements and international politics” (Burns and Eltham OSN by employing social bots, and how such manipulations 2009). Beside that, there was already a critical view upon will affect the discourse as a whole. Based on a sample of the influence of OSN’s as “tools” to express political opin- ca. -
An Examination of the Impact of Astroturfing on Nationalism: A
social sciences $€ £ ¥ Article An Examination of the Impact of Astroturfing on Nationalism: A Persuasion Knowledge Perspective Kenneth M. Henrie 1,* and Christian Gilde 2 1 Stiller School of Business, Champlain College, Burlington, VT 05401, USA 2 Department of Business and Technology, University of Montana Western, Dillon, MT 59725, USA; [email protected] * Correspondence: [email protected]; Tel.: +1-802-865-8446 Received: 7 December 2018; Accepted: 23 January 2019; Published: 28 January 2019 Abstract: One communication approach that lately has become more common is astroturfing, which has been more prominent since the proliferation of social media platforms. In this context, astroturfing is a fake grass-roots political campaign that aims to manipulate a certain audience. This exploratory research examined how effective astroturfing is in mitigating citizens’ natural defenses against politically persuasive messages. An experimental method was used to examine the persuasiveness of social media messages related to coal energy in their ability to persuade citizens’, and increase their level of nationalism. The results suggest that citizens are more likely to be persuaded by an astroturfed message than people who are exposed to a non-astroturfed message, regardless of their political leanings. However, the messages were not successful in altering an individual’s nationalistic views at the moment of exposure. The authors discuss these findings and propose how in a long-term context, astroturfing is a dangerous addition to persuasive communication. Keywords: astroturfing; persuasion knowledge; nationalism; coal energy; social media 1. Introduction Astroturfing is the simulation of a political campaign which is intended to manipulate the target audience. Often, the purpose of such a campaign is not clearly recognizable because a political effort is disguised as a grassroots operation. -
Shaping News -- 1 --Media Power
Shaping News – 1 Theories of Media Power and Environment Course Description: The focus in these six lectures is on how some facts are selected, shaped, and by whom, for daily internet, television, and print media global, national, regional, and local dissemination to world audiences. Agenda-setting, priming, framing, propaganda and persuasion are major tools to supplement basic news factors in various media environments. Course Goals and Student Learning Objectives: The overall goal is to increase student awareness that media filter reality rather than reflect it, and those selected bits of reality are shaped to be understood. Student learning objectives are: 1. Demonstrate how media environments and media structures determine what information is selected for dissemination; 2. Demonstrate how and why different media disseminate different information on the same situation or event; 3. Demonstrate how information is framed, and by whom, to access the media agenda. Required Texts/Readings: Read random essays and research online that focus on media news factors, agenda-setting and framing Assignments and Grading Policy: Two quizzes on course content plus a 20-page paper on a related, student- selected and faculty-approved research paper. Shaping News – 1 Media Environments and Media Power This is the first of six lectures on the shaping on news. It will focus on the theories of media environments based on the assumption that media are chameleon and reflect the governmental/societal system in which they exist. The remaining five lectures are on: (2) elements of news; (3) agenda-setting and framing; (4) propaganda; (5) attitude formation; and (6) cognitive dissonance. Two philosophical assumptions underlying the scholarly examination of mass media are that (1) the media are chameleons, reflecting their environment, and (2) their power is filtered and uneven. -
Automated Tackling of Disinformation
Automated tackling of disinformation STUDY Panel for the Future of Science and Technology European Science-Media Hub EPRS | European Parliamentary Research Service Scientific Foresight Unit (STOA) PE 624.278 – March 2019 EN Automated tackling of disinformation Major challenges ahead This study maps and analyses current and future threats from online misinformation, alongside currently adopted socio-technical and legal approaches. The challenges of evaluating their effectiveness and practical adoption are also discussed. Drawing on and complementing existing literature, the study summarises and analyses the findings of relevant journalistic and scientific studies and policy reports in relation to detecting, containing and countering online disinformation and propaganda campaigns. It traces recent developments and trends and identifies significant new or emerging challenges. It also addresses potential policy implications for the EU of current socio-technical solutions. ESMH | European Science-Media Hub AUTHORS This study was written by Alexandre Alaphilippe, Alexis Gizikis and Clara Hanot of EU DisinfoLab, and Kalina Bontcheva of The University of Sheffield, at the request of the Panel for the Future of Science and Technology (STOA). It has been financed under the European Science and Media Hub budget and managed by the Scientific Foresight Unit within the Directorate-General for Parliamentary Research Services (EPRS) of the Secretariat of the European Parliament. Acknowledgements The authors wish to thank all respondents to the online survey, as well as first draft, WeVerify, InVID, PHEME, REVEAL, and all other initiatives that contributed materials to the study. ADMINISTRATOR RESPONSIBLE Mihalis Kritikos, Scientific Foresight Unit To contact the publisher, please e-mail [email protected] LINGUISTIC VERSION Original: EN Manuscript completed in March 2019. -
Political Astroturfing Across the World
Political astroturfing across the world Franziska B. Keller∗ David Schochy Sebastian Stierz JungHwan Yang§ Paper prepared for the Harvard Disinformation Workshop Update 1 Introduction At the very latest since the Russian Internet Research Agency’s (IRA) intervention in the U.S. presidential election, scholars and the broader public have become wary of coordi- nated disinformation campaigns. These hidden activities aim to deteriorate the public’s trust in electoral institutions or the government’s legitimacy, and can exacerbate political polarization. But unfortunately, academic and public debates on the topic are haunted by conceptual ambiguities, and rely on few memorable examples, epitomized by the often cited “social bots” who are accused of having tried to influence public opinion in various contemporary political events. In this paper, we examine “political astroturfing,” a particular form of centrally co- ordinated disinformation campaigns in which participants pretend to be ordinary citizens acting independently (Kovic, Rauchfleisch, Sele, & Caspar, 2018). While the accounts as- sociated with a disinformation campaign may not necessarily spread incorrect information, they deceive the audience about the identity and motivation of the person manning the ac- count. And even though social bots have been in the focus of most academic research (Fer- rara, Varol, Davis, Menczer, & Flammini, 2016; Stella, Ferrara, & De Domenico, 2018), seemingly automated accounts make up only a small part – if any – of most astroturf- ing campaigns. For instigators of astroturfing, relying exclusively on social bots is not a promising strategy, as humans are good at detecting low-quality information (Pennycook & Rand, 2019). On the other hand, many bots detected by state-of-the-art social bot de- tection methods are not part of an astroturfing campaign, but unrelated non-political spam ∗Hong Kong University of Science and Technology yThe University of Manchester zGESIS – Leibniz Institute for the Social Sciences §University of Illinois at Urbana-Champaign 1 bots. -
Understanding Users' Perspectives of News Bots in the Age of Social Media
sustainability Article Utilizing Bots for Sustainable News Business: Understanding Users’ Perspectives of News Bots in the Age of Social Media Hyehyun Hong 1 and Hyun Jee Oh 2,* 1 Department of Advertising and Public Relations, Chung-Ang University, Seoul 06974, Korea; [email protected] 2 Department of Communication Studies, Hong Kong Baptist University, Kowloon Tong, Kowloon, Hong Kong SAR, China * Correspondence: [email protected] Received: 15 July 2020; Accepted: 10 August 2020; Published: 12 August 2020 Abstract: The move of news audiences to social media has presented a major challenge for news organizations. How to adapt and adjust to this social media environment is an important issue for sustainable news business. News bots are one of the key technologies offered in the current media environment and are widely applied in news production, dissemination, and interaction with audiences. While benefits and concerns coexist about the application of bots in news organizations, the current study aimed to examine how social media users perceive news bots, the factors that affect their acceptance of bots in news organizations, and how this is related to their evaluation of social media news in general. An analysis of the US national survey dataset showed that self-efficacy (confidence in identifying content from a bot) was a successful predictor of news bot acceptance, which in turn resulted in a positive evaluation of social media news in general. In addition, an individual’s perceived prevalence of social media news from bots had an indirect effect on acceptance by increasing self-efficacy. The results are discussed with the aim of providing a better understanding of news audiences in the social media environment, and practical implications for the sustainable news business are suggested. -
Teacher's Guide
Teacher’s Guide Propaganda: What’s the Message? Time Needed: One to two class periods Learning Objectives. Students will be able to: Materials Needed: Differentiate between forms of persuasive media. Student worksheets, Gallery Walk copies Identify bias, propaganda, and symbolism in media. Copy Instructions: Identify forms of propaganda in use. Student packet (Six pages double-sided; class set) Gallery Walk (One copy for the room) STEP BY STEP TEACHER PREP Place each page of the Gallery Walk around the classroom and divide the class into seven groups prior to teaching this lesson. (The groups will be rotating through these during class.) ANTICIPATE by asking students how they might try to convince someone to do something. (Examples: parents to extend curfew, teacher to postpone a due date, choice of movie with friends, etc.) Ask students if there are any common techniques. DISTRIBUTE one student packet to each student. READ through the packet with the class, answering questions or clarifying terms along the way if needed. DIVIDE students into up to seven small groups to rotate through the Gallery Walk pages. INSTRUCT students to spend 3-5 minutes at each station and complete the Gallery Walk pages in their student packet. (Tip: use an egg timer to keep track of the pace) If you have time for an 8th station, you can ask the students to stop at the challenge page as well. REVIEW the answers to the stations. ASSIGN students to complete the two Activity pages in their packet as review. CLOSE by asking students to think of all the places these propaganda techniques can be found. -
Supplementary Materials For
www.sciencemag.org/content/359/6380/1094/suppl/DC1 Supplementary Materials for The science of fake news David M. J. Lazer,*† Matthew A. Baum,* Yochai Benkler, Adam J. Berinsky, Kelly M. Greenhill, Filippo Menczer, Miriam J. Metzger, Brendan Nyhan, Gordon Pennycook, David Rothschild, Michael Schudson, Steven A. Sloman, Cass R. Sunstein, Emily A. Thorson, Duncan J. Watts, Jonathan L. Zittrain *These authors contributed equally to this work. †Corresponding author. Email: [email protected] Published 9 March 2018, Science 359, 1094 (2018) DOI: 10.1126/science.aao2998 This PDF file includes: List of Author Affiliations Supporting Materials References List of Author Affiliations David M. J. Lazer,1,2*† Matthew A. Baum,3* Yochai Benkler,4,5 Adam J. Berinsky,6 Kelly M. Greenhill,7,3 Filippo Menczer,8 Miriam J. Metzger,9 Brendan Nyhan,10 Gordon Pennycook,11 David Rothschild,12 Michael Schudson,13 Steven A. Sloman,14 Cass R. Sunstein,4 Emily A. Thorson,15 Duncan J. Watts,12 Jonathan L. Zittrain4,5 1Network Science Institute, Northeastern University, Boston, MA 02115, USA. 2Institute for Quantitative Social Science, Harvard University, Cambridge, MA 02138, USA 3John F. Kennedy School of Government, Harvard University, Cambridge, MA 02138, USA. 4Harvard Law School, Harvard University, Cambridge, MA 02138, USA. 5 Berkman Klein Center for Internet and Society, Cambridge, MA 02138, USA. 6Department of Political Science, Massachussets Institute of Technology, Cambridge, MA 02139, USA. 7Department of Political Science, Tufts University, Medford, MA 02155, USA. 8School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN 47405, USA. 9Department of Communication, University of California, Santa Barbara, Santa Barbara, CA 93106, USA. -
Frame Viral Tweets.Pdf
BIG IDEAS! Challenging Public Relations Research and Practice Viral Tweets, Fake News and Social Bots in Post-Factual Politics: The Case of the French Presidential Elections 2017 Alex Frame, Gilles Brachotte, Eric Leclercq, Marinette Savonnet [email protected] 20th Euprera Congress, Aarhus, 27-29th September 2018 Post-Factual Politics in the Age of Social Media 1. Algorithms based on popularity rather than veracity, linked to a business model based on views and likes, where novelty and sensationalism are of the essence; 2. Social trends of “whistle-blowing” linked to conspiracy theories and a pejorative image of corporate or institutional communication, which cast doubt on the neutrality of traditionally so-called expert figures, such as independent bodies or academics; 3. Algorithm-fuelled social dynamics on social networking sites which structure publics by similarity, leading to a fragmented digital public sphere where like-minded individuals congregate digitally, providing an “echo-chamber” effect susceptible to encourage even the most extreme political views and the “truths” upon which they are based. Fake News at the Presidential Elections Fake News at the Presidential Elections Fake News at the Presidential Elections Political Social Bots on Twitter Increasingly widespread around the world, over at least the last decade. Kremlin bot army (Lawrence Alexander on GlobalVoices.org; Stukal et al., 2017). DFRLab (Atlantic Council) Social Bots A “social bot” is: “a computer algorithm that automatically produces content and -
Empirical Comparative Analysis of Bot Evidence in Social Networks
Bots in Nets: Empirical Comparative Analysis of Bot Evidence in Social Networks Ross Schuchard1(&) , Andrew Crooks1,2 , Anthony Stefanidis2,3 , and Arie Croitoru2 1 Computational Social Science Program, Department of Computational and Data Sciences, George Mason University, Fairfax, VA 22030, USA [email protected] 2 Department of Geography and Geoinformation Science, George Mason University, Fairfax, VA 22030, USA 3 Criminal Investigations and Network Analysis Center, George Mason University, Fairfax, VA 22030, USA Abstract. The emergence of social bots within online social networks (OSNs) to diffuse information at scale has given rise to many efforts to detect them. While methodologies employed to detect the evolving sophistication of bots continue to improve, much work can be done to characterize the impact of bots on communication networks. In this study, we present a framework to describe the pervasiveness and relative importance of participants recognized as bots in various OSN conversations. Specifically, we harvested over 30 million tweets from three major global events in 2016 (the U.S. Presidential Election, the Ukrainian Conflict and Turkish Political Censorship) and compared the con- versational patterns of bots and humans within each event. We further examined the social network structure of each conversation to determine if bots exhibited any particular network influence, while also determining bot participation in key emergent network communities. The results showed that although participants recognized as social bots comprised only 0.28% of all OSN users in this study, they accounted for a significantly large portion of prominent centrality rankings across the three conversations. This includes the identification of individual bots as top-10 influencer nodes out of a total corpus consisting of more than 2.8 million nodes. -
Disinformation, and Influence Campaigns on Twitter 'Fake News'
Disinformation, ‘Fake News’ and Influence Campaigns on Twitter OCTOBER 2018 Matthew Hindman Vlad Barash George Washington University Graphika Contents Executive Summary . 3 Introduction . 7 A Problem Both Old and New . 9 Defining Fake News Outlets . 13 Bots, Trolls and ‘Cyborgs’ on Twitter . 16 Map Methodology . 19 Election Data and Maps . 22 Election Core Map Election Periphery Map Postelection Map Fake Accounts From Russia’s Most Prominent Troll Farm . 33 Disinformation Campaigns on Twitter: Chronotopes . 34 #NoDAPL #WikiLeaks #SpiritCooking #SyriaHoax #SethRich Conclusion . 43 Bibliography . 45 Notes . 55 2 EXECUTIVE SUMMARY This study is one of the largest analyses to date on how fake news spread on Twitter both during and after the 2016 election campaign. Using tools and mapping methods from Graphika, a social media intelligence firm, we study more than 10 million tweets from 700,000 Twitter accounts that linked to more than 600 fake and conspiracy news outlets. Crucially, we study fake and con- spiracy news both before and after the election, allowing us to measure how the fake news ecosystem has evolved since November 2016. Much fake news and disinformation is still being spread on Twitter. Consistent with other research, we find more than 6.6 million tweets linking to fake and conspiracy news publishers in the month before the 2016 election. Yet disinformation continues to be a substantial problem postelection, with 4.0 million tweets linking to fake and conspiracy news publishers found in a 30-day period from mid-March to mid-April 2017. Contrary to claims that fake news is a game of “whack-a-mole,” more than 80 percent of the disinformation accounts in our election maps are still active as this report goes to press. -
What Is Astroturfing? Churchofgodbigsandy.Com
What Is Astroturfing? The following information is from the “Edifying the Body” section of the Church of God Big Sandy’s website, churchofgodbigsandy.com. It was posted for the weekend of Dec. 10, 2016. Compiled by Dave Havir A definition titled “Astroturf” was posted at powerbase.info. Following is an excerpt of the definition. __________ “Astroturf” refers to grassroots groups or coalitions which are actually fake; often created or heavily funded by corporations, public relations firms, indus- try trade associations, and political interests. Astroturfing is used by organizations to give the illusion of genuine public support to their cause, manufacturing public opinion in what some commen- tators have called “democracy for hire.” As a deceptive use of third-party technique, Astroturfing can be considered a form of propaganda. Unlike genuine grassroots activism, which tends to be people-rich but cash- poor, Astroturf activism is normally people-poor but cash-rich. Astroturf campaigns work by recruiting the support of less-informed activists and individuals to their cause, often by means of deception. Astroturfing can mislead the public into believing that the views of the astro- turfer are mainstream and that widespread genuine support actually exists, when in most cases it does not. Deceptive Astroturf campaigns are thus most likely to occur where the interests of wealthy or powerful interests come into conflict with the interests of the public. ★★★★★ A definition titled “Astroturfing” was posted at weebly.com. Following is an excerpt of the definition. __________ “Astroturfing” denotes political, advertising, or public relations campaigns that are formally planned by an organization, but are disguised as sponta- neous, popular “grassroots” behavior.