- Disziplin: Sozial
- Forschungsmethode: Quantitativ
- Forschungsdesign: Primärerhebung, Weitere Daten (z. B. Einzelinterview, Web Scraping, Laborwerte etc.)
- Erhebungsstatus: Erhebung abgeschlossen, Ergebnisse veröffentlicht
Ziele der Studie
With their study, the scientists try to answer seven hypotheses, which are briefly summarized here:
- Posts about COVID-19 published on Telegram are more likely to contain conspiracy ideologies than those on Facebook (Hypothesis 1).
- It is assumed that those who post something about conspiracy ideologies tend to use negative and disparaging rhetoric more often on Telegram than on Facebook (Hypothesis 2).
- Statements by AfD and its members which were published on Facebook and which refer to conspiracy ideologies, generate more reactions than statements that do not (Hypothesis 3).
- Science skepticism is evident in right-wing populist pandemic communication on both Telegram and Facebook (Hypothesis 4).
- Right-wing populist actors tend to express negative reactions on social networks to governmental measures that intend to contain the pandemic, which then affects their readership and results in negative comments (Hypothesis 5).
- Individual political actors differ in their communication from political parties on social media. Their statements contain more radical rhetoric than those by official party appearances (Hypothesis 6).
- On Facebook, posts with personal content elicit stronger reactions (comments, likes) than posts with purely factual content (Hypothesis 7).
To investigate whether and how right-wing populist world views with conspiracy ideology are being transported through messages of right-wing populist politicians and celebrities on social media, a quantitative content analysis of Facebook and Telegram posts was conducted. Quantitative content analysis is one of the most common text analytical methods and has proven to be an effective research method to collect data (Bortz & Döring, 2006). The latter not only allows to quantify word material in terms of certain aspects in this case content, but also to analyse large amounts of material (Bortz & Döring, 2006). To ensure a rule-guided and intersubjectively verifiable analysis, the paper at hand followed steps which include, amongst others, the development of a codebook and testing of intercoder reliability through pretests, as described in the following section.
Especially social media posts and comments are examined through content analysis in regards to their populist messages. Previous quantitative content analysis with social media content has for example addressed the radicalization of political social media discourses (Riebe et al., 2018; Krämer et al., 2021), conspiracy ideologies in regards to viruses (Wood, 2018; Chen et al., 2020), or the portrayal of vaccines on social media (Guidry et al., 2015). To the best of our knowledge, the combination of content on Facebook and Telegram has yet to be analysed in the content analysis context our study is proposing.
The data from this study are not yet openly available for reuse. Please get in touch with the responsible person.