Analysing the social media perspective on the Russia–Ukraine conflict through the US right-leaning news lens

This study investigates how the public sentiment differs in online spaces when moving between different social media platforms even within the ecosystem of right-leaning or right-wing, with the context being the ongoing Russia–Ukraine conflict that began in February 2022, along the lines of Mullen 2006 stressing the importance of informal political discourse. Through the use of qualitative analysis by artificial intelligence (AI) as well as manual input, the work analyses the comments sections of posts by mainstream American right-leaning/right-wing news media outlets across various social media and along the timespan of the war, with the work looking at all the comments, not just American. The selection of news outlets was done through combining a research article on what constituted mainstream media from the Pew Research Center and the Ground News bias classifications. The second point of interest for the research is to observe whether the linguistics models employed by the AI software (ATLAS.Ti in this case) hold up when it comes to analysis of comments. The most interesting result was how spectacularly the AI software failed when it came to categorizing sarcasm, with a 0 per cent success rate in this venture, implying that the linguistic models used are still inadequate for such purposes. When it comes to analysing political trends between social media platforms, the major observation was that the Facebook comments sections always had the least pro-Ukraine/anti-Russian sentiment. The pervasive sentiment, however, appeared to be the commenters’ disapproval of sending financial aid to Ukraine over using the same money to improve living conditions at home.