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The article examines false information in digital media as a sociotechnical phenomenon that is shaped at the intersection of content distortions, producer intent, and networked platform mechanisms of diffusion. Given the blurred nature of the everyday use of the terms fake and fake news, a conceptual delimitation of related phenomena is undertaken, and the tendency to universalise these concepts across different types of falsehood is critically analysed.

The article considers an approach to detecting fake news in the digital environment through text analysis using machine learning and natural language processing methods. The proposed method is based on a hybrid text representation combining frequency features (TF-IDF) and contextual embeddings obtained using the IBM Granite model. A complete data processing cycle was developed, covering the stages of exploratory analysis (EDA), text preprocessing and tokenization, forming vector representations, training a logistic regression model, and obtaining key metrics.

The article describes a study of identification of fake news based on natural language processing, big data analysis and deep learning technology. The developed system automatically checks the news for signs of fake news, such as the use of manipulative language, unverified sources and unreliable information. Data visualization is implemented on the basis of a friendly user interface that displays the results of news analysis in a convenient and understandable format.

The article is devoted to the study of popular global news telegram-channels, their impact on society, and the identification of advantages and disadvantages of this media format. The article examines prominent news channels such as The New York Times, BBC News, The Guardian, CNN and Reuters. Their features and differences are analyzed, the positive and negative aspects of using Telegram channels to receive news and information are described.

The article considers the use of words of foreign origin in administrative legislation which often consciously or unconsciously replace the words of the Ukrainian language that negatively affects the explanation of legal relations and their legal regulation. It is noted that unverified facts are published through the media, which encourages them to verify by establishing the actual existence of a fact and its legal assessment.

Information wars have long been used as a full-fledged weapon against the enemy, using both manipulation and completely fake messages. The methods used to disseminate false media messages by their authors are completely different, but the goal is almost always the same - to make the target audience that consumes information, believe and be influenced.

The article describes the characteristics of “fake”, “fake news”. The manipulative technologies in the media are considered. According to the author, today the users of social networks constantly see false information, written and disseminated in order to increase internet traffic.

The first mention of fake news comes from the seventeenth century. Newspaper duck — this is what they call false, falsified and unverified information distributed in the media. According to one version (and many of them), the occurrence of the expression is associated with an anecdote of the Belgian journalist Cornelissen, who once published quite seriously, as if a scientific message, an anecdote about the greed of ducks. Some scientist chopped, say, a duck into small pieces and gave “for breakfast” to other nineteen ducks.

The article deals with memes as expressive rhetorical resource in media representations of the Russian-Ukrainian hybrid war and military conflict. It explores textual slogans of Russian propaganda that serve to legitimize external aggression. When these units are mirrored as intertextual material in the Ukrainian counter-discourse, they become critical targets for deconstructing fakes and decontamination of manipulative programs. The network of memetic signs is subordinated to the task of symbolic identification of conflict sides and their objectives.

The notion of misinformation revealed difference misinformation and fake. The classification of fake on the various grounds is made, it is also found out the types of information to spread on the Internet. The essence and origin of the term “fake” describes the creation and dissemination of fake information in the social media. The typical examples of fake information in the Ukrainian media space, revealed the impact of such messages to users of social networks.