University of Kwazulu-Natal

Pdf Russian Disinformation Efforts On Social Media Rand Corporation

Bonisiwe Shabane
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pdf russian disinformation efforts on social media rand corporation

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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.

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This Material May Be Protected By Copyright Law (Title 17

This material may be protected by copyright law (Title 17 U.S. Code). Uploaded by TV Archive on March 16, 2019 Your use of JSTOR indicates your acceptance of the Terms & Conditions of Use and the Privacy Policy. Use your account to permanently save your acceptance. Academia.edu no longer supports Internet Explorer.

To Browse Academia.edu And The Wider Internet Faster And More

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 lear...

For More Information, Visit Www.rand.org/about/principles. RAND's Publications Do Not Necessarily

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....

A Mixed Methodology Is Used, Combining Qualit... Social Media Have

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....

The Case Study Is The Infodemic Generated On Social Media

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 firs...