JOURNAL ARTICLE
The New Pravda: How US Media Is Morphing into One Politically Slanted News Organization.
Published In: Journal of Communication & Media Studies (2470-9247), 2024, v. 9, n. 2. P. 1 1 of 3
Database: Communication Source 2 of 3
Authored By: Lindoo, Ed 3 of 3
Abstract
In the early 1700s and throughout the 1900s, newspapers emerged worldwide. Apprenticeships were abundant as many young individuals pursued higher education to become writers, undergoing specialized training in ethics and accurate reporting. This trend persisted for most of the world into the early 2000s, excluding communist Russia and other countries under communist or dictatorship rule. In Russia, the state newspaper, named Pravda, was written and controlled by the communist party. Pravda served as the sole source of news the Russian people, all of which adhered to the party's narrative. The late 1990s saw the rise of the internet, introducing a new information format known as social media, including platforms like Twitter and Facebook, lacking a solid foundation. This prompted traditional news channels, such as CNN, MSNBC, and FOX, to sensationalize the news to attract a larger audience. Due to the political leanings of these organizations, the entire America news system appears to be transforming into one big "Pravda." The objective of this research is to examine historical patterns and illustrate the potential trajectory of the United States' landscape and, possibly, its impact globally. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Communication & Media Studies (2470-9247). 2024/12, Vol. 9, Issue 2, p1
- Document Type:Article
- Subject Area:History
- Publication Date:2024
- ISSN:2470-9247
- DOI:10.18848/2470-9247/CGP/v09i02/1-23
- Accession Number:182007027
- Copyright Statement:Copyright of Journal of Communication & Media Studies (2470-9247) is the property of Common Ground Research Networks and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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