509 research outputs found

    A New application of Social Impact in Social Media for overcoming fake news in health

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    One of the challenges today is to face fake news (false information) in health due to its potential impact on people's lives. This article contributes to a new application of social impact in social media (SISM) methodology. This study focuses on the social impact of the research to identify what type of health information is false and what type of information is evidence of the social impact shared in social media. The analysis of social media includes Reddit, Facebook, and Twitter. This analysis contributes to identifying how interactions in these forms of social media depend on the type of information shared. The results indicate that messages focused on fake health information are mostly aggressive, those based on evidence of social impact are respectful and transformative, and finally, deliberation contexts promoted in social media overcome false information about health. These results contribute to advancing knowledge in overcoming fake health-related news shared in social media

    Ups and downs on “r/science” — exploring the dynamics of science communication on Reddit

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    This exploratory study analyzed user-generated science communication on Reddit from May 2007 to October 2018 (n = 694.147 posts). We used automated content analyses and topic modelling to explore patterns that the user-generated communication exhibits. Results indicate that science communication on r/science refers to a broad range of different topics and disciplines. Specific upvote features of Reddit result in increased attention to sources and topics. Especially, social media sources and content that is self-referential to Reddit lead to high controversy in discussions

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

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    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

    Identification and Modeling Social Media Influence Pathways: a Characterization of a Disinformation Campaign Using the Flooding-the-zone Strategy via Transfer Entropy

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    The internet has made it easy for narratives to spread quickly and widely without regard for accuracy or the harm they may cause to society. Unfortunately, this has led to the rise of bad actors who use fake and misleading articles to spread harmful misinformation. These actors flood the information space with low-quality articles in an effort to disrupt opposing narratives, sow confusion, and discourage the pursuit of truth. In societies that prioritize free speech, maintaining control over the information space remains a persistent challenge. Achieving this requires strategic planning to protect the dissemination of information in ways that promote dialogue towards organic consensus building and protect users from undue manipulation from foreign adversarial state actors. The objective of this dissertation is to investigate how bad actors can manipulate the information space in societies that value free speech. To achieve this objective, we will define the different narratives used to flood the information space, identify the controversial elements that contribute to their spread, and analyze the actors involved in promoting these narratives and their levels of influence. To gain a deeper understanding of the dynamics that underlie information space flooding, we will examine the flow of influence from news organizations to online users across multiple social networks, and explore the formation of online communities and echo chambers that align with specific narratives. We will also investigate the role of controversiality in information and influence spread, specifically examining how controversial authors tend to be sources of influence in these networks. By addressing these objectives, we hope to provide an analysis of the ways in which bad actors can manipulate the information space. Furthermore, we aim to provide insights into how we can develop strategies to counteract these efforts and protect the integrity of the information ecosystem. Through our investigation, we hope to contribute to the growing body of research focused on understanding and addressing the challenges posed by bad actors in the information space

    Disciplinary Rhetoric: And the Language of Online Rape Culture

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    Get Out of the Nest! Drivers of Social Influence in the #TwitterMigration to Mastodon

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    The migration of Twitter users to Mastodon following Elon Musk's acquisition presents a unique opportunity to study collective behavior and gain insights into the drivers of coordinated behavior in online media. We analyzed the social network and the public conversations of about 75,000 migrated users and observed that the temporal trace of their migrations is compatible with a phenomenon of social influence, as described by a compartmental epidemic model of information diffusion. Drawing from prior research on behavioral change, we delved into the factors that account for variations across different Twitter communities in the effectiveness of the spreading of the influence to migrate. Communities in which the influence process unfolded more rapidly exhibit lower density of social connections, higher levels of signaled commitment to migrating, and more emphasis on shared identity and exchange of factual knowledge in the community discussion. These factors account collectively for 57% of the variance in the observed data. Our results highlight the joint importance of network structure, commitment, and psycho-linguistic aspects of social interactions in describing grassroots collective action, and contribute to deepen our understanding of the mechanisms driving processes of behavior change of online groups
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