Browsing by Subject "Russian propaganda"

This thesis examines computational propaganda techniques employed by RT (Russia Today) on Twitter by analyzing tweet sentiment and propaganda dynamics. Through quantitative analysis of RT English tweets spanning a decade, the study reveals RT’s strategies in terms of sentiment manipulation, including positive portrayals of Russia and Putin and demonization of adversaries. It further identifies a discernible political bias in RT’s coverage of international relations. The analysis also explores changes in country depictions within RT reports over the past ten years, highlighting the stability of RT’s narratives towards Putin, which suggests the importance of maintaining Putin’s image for Russian state-owned media. Moreover, the study identifies a correlation between the sentiment of tweets related to Russia, the extent of coverage of Putin, and Putin's approval ratings, shedding light on the dynamic nature of RT propaganda and its possible influencing factors. In terms of methodology, machine learning and dictionary-based approaches conducted in sentiment classification yield robust results, indicating the potential of computational methods in social science studies. In general, the research contributes to the understanding of modern propaganda and offers insights into the application of artificial intelligence in social science.