Combating Foreign Disinformation On Social Media Series

Bonisiwe Shabane
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combating foreign disinformation on social media series

Academia.edu no longer supports Internet Explorer. To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser. The RAND Corporation is a research organization that develops solutions to public policy challenges to help make communities throughout the world safer and more secure, healthier and more prosperous. RAND is nonprofit, nonpartisan, and committed to the public interest. To learn more about RAND, visit www.rand.org. Research Integrity Our mission to help improve policy and decisionmaking through research and analysis is enabled through our core values of quality and objectivity and our unwavering commitment to the highest level of integrity...

To help ensure our research and analysis are rigorous, objective, and nonpartisan, we subject our research publications to a robust and exacting quality-assurance process; avoid both the appearance and reality of financial and other... For more information, visit www.rand.org/about/principles. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors. The dissemination of purposely deceitful or misleading content to target audiences for political aims or economic purposes constitutes a threat to democratic societies and institutions, and is being increasingly recognized as a major security... Disinformation can also be part of hybrid threat activities. This research paper examines findings on the effects of disinformation and addresses the question of how effective counterstrategies against digital disinformation are, with the aim of assessing the impact of responses such as the...

The paper’s objective is to synthetize the main scientific findings on disinformation effects and on the effectiveness of debunking, inoculation, and forewarning strategies against digital disinformation. A mixed methodology is used, combining qualit... Social media have democratized communication but have led to the explosion of the socalled "fake news" phenomenon. This problem has visible implications on global security, both political (e.g.the QANON case) and health (anti-Covid vaccination and No-Vax fake news). Models that detect the problem in real time and on large amounts of data are needed. Digital methods and text classification procedures are able to do this through predictive approaches to identify a suspect message or author.

This paper aims to apply a supervised model to the study of fake news on the Twittersphere to highlight its potential and preliminary limitations. The case study is the infodemic generated on social media during the first phase of the COVID-19 emergency. The application of the supervised model involved the use of a training and testing dataset. The different preliminary steps to build the training dataset are also shown, highlighting, with a critical approach, the challenges of working with supervised algorithms. Two aspects emerge. The first is that it is important to block the sources of bad information, before the information itself.

The second is that algorithms could be sources of bias. Social media companies need to be very careful about relying on automated classification. The Disinformation Pandemic: A Deep Dive into the Challenges and Collaborative Solutions Social media, once hailed as a revolutionary tool for connection and information sharing, has increasingly become a breeding ground for disinformation, the deliberate spread of false or misleading information. This "infodemic" poses a significant threat to democratic processes, societal cohesion, and trust in institutions. From undermining elections to fueling social unrest and eroding public health, the consequences of disinformation are far-reaching and demand immediate attention.

The motivations behind disinformation campaigns are diverse. Some actors spread conspiracy theories and divisive narratives for ideological reasons or personal amusement. Political actors might engage in disinformation to sway public opinion in their favor, while foreign adversaries may seek to destabilize other nations or advance their geopolitical agendas. Financially motivated actors spread scams and clickbait for profit, whereas competitors might aim to tarnish the reputations of rivals. Understanding these varied motivations is crucial for developing effective countermeasures. The rapid growth of disinformation is driven by several factors.

Social media algorithms often prioritize sensational and emotionally charged content, inadvertently amplifying false information. Studies have shown that fake news spreads significantly faster and wider than factual information on these platforms. Moreover, the emergence of generative AI has made it easier than ever to create highly convincing deepfakes, synthetic images, and fabricated text, blurring the lines between reality and fiction. The proliferation of AI-powered bots further exacerbates the problem, flooding social media with automated disinformation campaigns that reach vast audiences. Combating this infodemic requires a concerted and collaborative effort. Social media platforms, governments, organizations, and individuals all have a crucial role to play in prioritizing truth and mitigating the spread of disinformation.

Download the free Kindle app and start reading Kindle books instantly on your smartphone, tablet, or computer - no Kindle device required. Read instantly on your browser with Kindle for Web. Using your mobile phone camera - scan the code below and download the Kindle app. How are state adversaries using disinformation on social media to advance their interests? What does the joint force?and the U.S. Air Force in particular?need to be prepared to do in response?

Disinformation campaigns on social media pose a nuanced threat to the United States, but the response remains ad hoc and uncoordinated. This series overview presents recommendations to better prepare for this new age of information warfare. Customer Reviews, including Product Star Ratings help customers to learn more about the product and decide whether it is the right product for them.

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Academia.edu No Longer Supports Internet Explorer. To Browse Academia.edu And

Academia.edu no longer supports Internet Explorer. To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser. The RAND Corporation is a research organization that develops solutions to public policy challenges to help make communities throughout the world safer and more secure, healthier and more prosperous. RAND is nonprofit, nonpart...

To Help Ensure Our Research And Analysis Are Rigorous, Objective,

To help ensure our research and analysis are rigorous, objective, and nonpartisan, we subject our research publications to a robust and exacting quality-assurance process; avoid both the appearance and reality of financial and other... For more information, visit www.rand.org/about/principles. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors. The dis...

The Paper’s Objective Is To Synthetize The Main Scientific Findings

The paper’s objective is to synthetize the main scientific findings on disinformation effects and on the effectiveness of debunking, inoculation, and forewarning strategies against digital disinformation. A mixed methodology is used, combining qualit... Social media have democratized communication but have led to the explosion of the socalled "fake news" phenomenon. This problem has visible implic...

This Paper Aims To Apply A Supervised Model To The

This paper aims to apply a supervised model to the study of fake news on the Twittersphere to highlight its potential and preliminary limitations. The case study is the infodemic generated on social media during the first phase of the COVID-19 emergency. The application of the supervised model involved the use of a training and testing dataset. The different preliminary steps to build the training...

The Second Is That Algorithms Could Be Sources Of Bias.

The second is that algorithms could be sources of bias. Social media companies need to be very careful about relying on automated classification. The Disinformation Pandemic: A Deep Dive into the Challenges and Collaborative Solutions Social media, once hailed as a revolutionary tool for connection and information sharing, has increasingly become a breeding ground for disinformation, the deliberat...