Fake News in Metajournalistic Discourse
نویسندگان
چکیده
In recent years, fake news has become central to debates about the state and future of journalism. This article examines imaginaries around as a threat democracy role journalism in mitigating this threat. The study builds on 34 qualitative interviews with Danish journalists, media experts, government officials, social company representatives well 42 editorials from nine national outlets. Drawing discourse theory concept metajournalistic discourse, analysis finds that actors mobilise support opposing discursive positions its relationship falsehoods. While some voices articulate established journalistic values, such objectivity, antithesis news, others blame contemporary practices for potentially contributing misinformation, calling change reform. These contrasts are particularly notable between public stances editors-in-chief, expressed through editorials, reflections based personal experience reporters experts. paper concludes functions floating signifier mobilised not only attack or defend journalism, but also present conflicting visions what is ought be.
منابع مشابه
Fake News in Social Networks
We model the spread of news as a social learning game on a network. Agents can either endorse or oppose a claim made in a piece of news, which itself may be either true or false. Agents base their decision on a private signal and their neighbors’ past actions. Given these inputs, agents follow strategies derived via multi-agent deep reinforcement learning and receive utility from acting in acco...
متن کاملAutomatic Detection of Fake News
The proliferation of misleading information in everyday access media outlets such as social media feeds, news blogs, and online newspapers have made it challenging to identify trustworthy news sources, thus increasing the need for computational tools able to provide insights into the reliability of online content. In this paper, we focus on the automatic identification of fake content in online...
متن کاملFake News, Real Consequences: Recruiting Neural Networks for the Fight Against Fake News
The Fake News Challenge (FNC-1) is a public competition that aims to find automatic methods for detecting fake news. The dataset for the challenge consists of headline-body pairs, with the objective being to classify the pairs as unrelated, agreeing, disagreeing, or discussing. We developed four neural network models for FNC-1, two using a feed-forward architecture and two using a recurrent arc...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journalism Studies
سال: 2023
ISSN: ['1469-9699', '1461-670X']
DOI: https://doi.org/10.1080/1461670x.2023.2167106