Suchergebnisse

В статье рассматривается Резолюция ЦК КПК, в которой описывается партийная идеология и политическая концепция нового руководства Китая с использованием политических метафор. ; On November 11, 2021, the Sixth Plenary Session of the 19th Central Committee of the Communist Party of China adopted the "Resolution of the Central Committee of the Communist Party of China on the Major Achievements and Historical Experience of the Party's Hundred Years of Struggle" (hereinafter referred to as the Resolution). As an important document passed at the confluence of the "two centenary" goals, the Resolution has an extraordinary historical status. It conveys the party's ruling ideology and expresses the political concept of China's new leadership through political metaphors, thereby realizing communication between the country and the people.

This study investigates the types of misinformation spread on Twitter that evokes scientific authority or evidence when making false claims about the antimalarial drug hydroxychloroquine as a treatment for COVID-19. Specifically, we examined tweets generated after former U.S. President Donald Trump retweeted misinformation about the drug using an unsupervised machine learning approach called the biterm topic model that is used to cluster tweets into misinformation topics based on textual similarity. The top 10 tweets from each topic cluster were content coded for three types of misinformation categories related to scientific authority: medical endorsements of hydroxychloroquine, scientific information used to support hydroxychloroquine's use, and a comparison group that included scientific evidence opposing hydroxychloroquine's use. Results show a much higher volume of tweets featuring medical endorsements and use of supportive scientific information compared to accurate and updated scientific evidence, that misinformation-related tweets propagated for a longer time frame, and the majority of hydroxychloroquine Twitter discourse expressed positive views about the drug. Metadata from Twitter accounts found that prominent users within misinformation discourse were more likely to have media or political affiliation and explicitly expressed support for President Trump. Conversely, prominent accounts within the scientific opposition discourse primarily consisted of medical doctors or scientists but had far less influence in the Twitter discourse. Implications of these findings and connections to related social media research are discussed, as well as cognitive mechanisms for understanding susceptibility to misinformation and strategies to combat misinformation spread via online platforms.