The recent research in the field of social media analysis and moderation is focusing on several critical areas, including the long-term sustainability of online collaborations, the distinction between sarcasm and cyberbullying, the spread and impact of fake news, and the management of toxicity in social media platforms. Innovations in machine learning and natural language processing are being leveraged to address these challenges, with notable advancements in predicting the longevity of collaborative projects, differentiating harmful content from sarcasm, and modeling the diffusion of fake news. Additionally, there is a growing emphasis on multi-layer network analysis to understand deliberation in online discussions and the development of machine learning-guided systems for community content moderation to enhance decision consistency. These developments collectively aim to create safer and more sustainable online environments, particularly by addressing the vulnerabilities of specific user groups and improving the detection and moderation of harmful content.