Typology, Etiology, and Fact-Checking: A Pathological Study of Top Fake News in China

Disinformation and Artificial Intelligence: the Case of Online Journalism in China

“…From our review, we perceive that there are symbolic residues from the offline culture which are being transferred to the online perceptions. For example, fake news typology follows a distinctive path, as there is a prevalence of topics linked to social aspects and entertainment (Wang et al, 2022), in opposition to the Western countries, where the same authors remark that disinformation is mainly related to political affairs.…”

“…At the same time, AI enables also the possibility to detect disinformation (Kaplan, 2020), when the process is guided by professionals. This feature can be very interesting in a country like China, where rumours are forbidden in media (Guo, 2020), and individual fact-checking requires a heavy investment of time (Xu & Gutsche, 2021), or it is not commonly performed (Wang et al, 2022), due to the link between media and political institutions and leaders. To do this, we agree with Xi & Latif (2022) that a "double gatekeeping" (p. 41) is needed, the first gatekeeping should be performed from the machine, to the sources; and the second one should be completed from a professional to the machine results.…”

“…In an authoritarian context, disinformation is controversial. Rumours are frequently described as fake news (Wang et al, 2022), but they play an important role as a political expression (Guo, 2020), even though they are banned from being published in media. As Guo (2020) demonstrated, rumors continue to be spread online, even on public media, when they do not include political implications.…”

“…It is also relevant in this line of research to consider the studies connected with the message features. Wang et al (2022) reviewed the characteristics of fake news in China from 2001 to 2019. To do so, the authors examined, using content analysis, 189 relevant fake news published by the Shanghai Journalism Review.…”

Трамп, Твиттер и фейковые новости (Trump, Twitter and Fake News)

“…2018). Другие добавили несколько типологий, таких как клик-приманка (click-bait), слухи, субъективные предположения, тревожные разговоры, новости пользовательского контента и новости с ложными данными (Wang, Rao, & and Sun, 2020). Однако для целей этого анализа авторы используют типологии из Доклада Совета Европы: сатира или пародия, вводящий в заблуждение контент, ложный контент, манипулируемый контент, ложный контекст, ложные связи и ложный контент (Wardle & Derakhshan, 2017).…”