The Future of Cyber-Enabled Influence Operations: Emergent Technologies, Disinformation, and the Destruction of Democracy

Nation-states have been embracing online influence campaigns through disinformation at breakneck speeds. Countries such as China and Russia have completely revamped their military doctrine to information-first platforms [1, 2] (Mattis, Peter. (2018). China’s Three Warfares in Perspective. War on the Rocks. Special Series: Ministry of Truth. https://warontherocks.com/2018/01/chinas-three-warfares-perspective/, Cunningham, C. (2020). A Russian Federation Information Warfare Primer. Then Henry M. Jackson School of International Studies. Washington University. https://jsis.washington.edu/news/a-russian-federation-information-war fare-primer/.) to compete with the United States and the West. The Chinese principle of “Three Warfares” and Russian Hybrid Warfare have been used and tested across the spectrum of operations ranging from competition to active conflict. With the COVID19 pandemic limiting most means of face-to-face interpersonal communi-cation, many other nations have transitioned to online tools to influence audiences both domestically and abroad [3] (Strick, B. (2020). COVID-19 Disinformation: Attempted Influence in Disguise. Australian Strategic Policy Institute. International Cyber Policy Center. https://www.aspi.org.au/report/covid-19-disinformation.) to create favorable environments for their geopolitical goals and national objectives. This chapter focuses on the landscape that allows nations like China and Russia to attack democratic institutions and discourse within the United States, the strategies and tactics employed in these campaigns, and the emergent technologies that will enable these nations to gain an advantage with key populations within their spheres of influence or to create a disadvantage to their competitors within their spheres of influence. Advancements in machine learning through generative adversarial networks [4] (Creswell, A; White, T; Dumoulin, V; Arulkumaran, K; Sengupta, B; Bharath, A. (2017) Generative Adversarial Networks: An Overview. IEE-SPM. April 2017. https://arxiv.org/pdf/1710.07035.pdf.) that create deepfakes [5] (Whit-taker, L; Letheren, K; Mulcahy, R. (2021). The Rise of Deepfakes: A Conceptual J. Littell envelope symbolenvelope symbolenvelope symbol Army Cyber Institute at the West Point, United States Military Academy, West Point, NY 10996, USA e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 A.Farhadietal. (eds.), The Great Power Competition Volume 3, https://doi.org/10.1007/978-3-031-04586-8_10 197 198 J. Littell Framework and Research Agenda for Marketing. https://journals.sagepub.com/doi/ abs/10.1177/1839334921999479.) and attention-based transformers [6](https:// arxiv.org/abs/1810.04805.) (Devlin et al., 2018) that create realistic speech patterns and interaction will continue to plague online discussion and information spread, attempting to cause further partisan divisions and decline of U.S. stature on the world stage and democracy as a whole.https://digitalcommons.usmalibrary.org/aci_books/1020/thumbnail.jp

Mapping (Dis-)Information Flow about the MH17 Plane Crash

Digital media enables not only fast sharing of information, but also disinformation. One prominent case of an event leading to circulation of disinformation on social media is the MH17 plane crash. Studies analysing the spread of information about this event on Twitter have focused on small, manually annotated datasets, or used proxys for data annotation. In this work, we examine to what extent text classifiers can be used to label data for subsequent content analysis, in particular we focus on predicting pro-Russian and pro-Ukrainian Twitter content related to the MH17 plane crash. Even though we find that a neural classifier improves over a hashtag based baseline, labeling pro-Russian and pro-Ukrainian content with high precision remains a challenging problem. We provide an error analysis underlining the difficulty of the task and identify factors that might help improve classification in future work. Finally, we show how the classifier can facilitate the annotation task for human annotators

Right Across the World

In a post-Trump world, the right is still very much in power. Significantly more than half the world’s population currently lives under some form of right-wing populist or authoritarian rule. Today’s autocrats are, at first glance, a diverse band of brothers. But religious, economic, social and environmental differences aside, there is one thing that unites them - their hatred of the liberal, globalised world. This unity is their strength, and through control of government, civil society and the digital world they are working together across borders to stamp out the left. In comparison, the liberal left commands only a few disconnected islands - Iceland, Mexico, New Zealand, South Korea, Spain and Uruguay. So far they have been on the defensive, campaigning on local issues in their own countries. This narrow focus underestimates the resilience and global connectivity of the right. In this book, John Feffer speaks to world’s leading activists to show how international leftist campaigns must come together if they are to combat the rising tide of the right. A global Green New Deal, progressive trans-European movements, grassroots campaigning on international issues with new and improved language and storytelling are all needed if we are to pull the planet back from the edge of catastrophe. This book is both a warning and an inspiration to activists terrified by the strengthening wall of far-right power

Struggling to Remember: Perceptions, Potentials and Power in an Age of Mediatised Memory

What role do new, networked and pervasive technologies play in changing individual and collective memory processes? Many recent debates have focused on whether we are in the online era remembering ‘less’ or ‘more’ – informed, perhaps, by a tendency to think of memory spatially and quantifiably as working like an archive. Drawing on the philosophical theorising of Henri Bergson and its development through Gilbert Simondon, this thesis makes two interventions into the field. Firstly, conceptually, it establishes a process-based approach to perception, memory and consciousness in a shift away from the archive metaphor – thinking memory not as informing ‘knowledge of the past’ but ‘action in duration’. It situates the conscious, living being as transindividual – affectively relational to its perceived bodily and social environments, through psychic and collective individuation respectively. Moreover, it considers technologies as forms of transindividual extension of consciousness. Furthermore, it proposes the ‘antimetaphor’ of the anarchive as a conceptual tool with which to understand these durationbased, bodily and technological, action-oriented processes. Secondly, methodologically, it advocates a rephrasing of the question from how much we are remembering to how we are remembering differently. Armed now with a developed theoretical position and methodological approach, the thesis explores through three case-study chapters how personal and more historical pasts may be remembered, individually and more collectively, through new, prevalent technologies of memory such as search engines, forums and social-media sites. Analysing the material experiences of remembering, as well as examining the economic drives of the platforms and wider actors, and the resulting socio-political implications, the thesis sets out the original argument of a contemporary struggle for memory: a complex negotiation of tensions between agencies of the body, the social, and the multifarious and interconnected socio-political and economic interests of the technological platforms and hybridised media systems through which contemporary remembering increasingly takes place

Rethinking Social Media and Extremism

Terrorism, global pandemics, climate change, wars and all the major threats of our age have been targets of online extremism. The same social media occupying the heartland of our social world leaves us vulnerable to cybercrime, electoral fraud and the 'fake news' fuelling the rise of far-right violence and hate speech. In the face of widespread calls for action, governments struggle to reform legal and regulatory frameworks designed for an analogue age. And what of our rights as citizens? As politicians and lawyers run to catch up to the future as it disappears over the horizon, who guarantees our right to free speech, to free and fair elections, to play video games, to surf the Net, to believe ‘fake news’? Rethinking Social Media and Extremism offers a broad range of perspectives on violent extremism online and how to stop it. As one major crisis follows another and a global pandemic accelerates our turn to digital technologies, attending to the issues raised in this book becomes ever more urgent

Linguistic variation across Twitter and Twitter trolling

Trolling is used to label a variety of behaviours, from the spread of misinformation and hyperbole to targeted abuse and malicious attacks. Despite this, little is known about how trolling varies linguistically and what its major linguistic repertoires and communicative functions are in comparison to general social media posts. Consequently, this dissertation collects two corpora of tweets – a general English Twitter corpus and a Twitter trolling corpus using other Twitter users’ accusations – and introduces and applies a new short-text version of Multi-Dimensional Analysis to each corpus, which is designed to identify aggregated dimensions of linguistic variation across them. The analysis finds that trolling tweets and general tweets only differ on the final dimension of linguistic variation, but share the following linguistic repertoires: “Informational versus Interactive”, “Personal versus Other Description”, and “Promotional versus Oppositional”. Moreover, the analysis compares trolling tweets to general Twitter’s dimensions and finds that trolling tweets and general tweets are remarkably more similar than they are different in their distribution along all dimensions. These findings counter various theories on trolling and problematise the notion that trolling can be detected automatically using grammatical variation. Overall, this dissertation provides empirical evidence on how trolling and general tweets vary linguistically