The field of social media and political discourse is rapidly evolving, with a growing focus on understanding the nuances of online interactions and their impact on societal trends. Recent studies have highlighted the importance of analyzing the prevalence and engagement of negative news posts, the role of large language models in detecting populist discourse, and the effects of algorithmic changes on news visibility. Additionally, researchers are exploring the use of semantic similarity and topic trajectory analysis to study disinformation narratives and the manifestation of toxicity in online discussions. The development of new tools and methodologies, such as the Tweet Narrative Analysis Dashboard, is also enabling more effective analysis of social media data. Noteworthy papers in this area include: The paper on Identifying Fine-grained Forms of Populism in Political Discourse, which demonstrates the limitations of large language models in detecting populist discourse and highlights the importance of fine-tuned classifiers. The study on Changes to the Facebook Algorithm, which shows that algorithmic changes can significantly impact news visibility and user engagement. The thesis on Studying Disinformation Narratives on Social Media, which develops a continuous scale measurement of similarity to disinformation narratives and demonstrates its effectiveness in detecting nuanced disinformation.