In an era where social media platforms play a crucial role in shaping public discourse, microblogging data emerges as a vital resource for understanding complex social interactions. This paper introduces MTNSA (Microblogging Text Network Sentiment Analysis), a groundbreaking approach that harnesses the richness of social media communication by analyzing three separate categories: the relationships between words, relationships between hashtags, and relationships between emojis. MTNSA utilizes innovative techniques leveraging network theory to unravel the thoughts and opinions in microblogging environments, enriching itself by integrating sentiment analysis into this framework. This innovative method provides a comprehensive view of the sentiments associated with each node, offering deeper insights into the emotional nuances of online discourse. MTNSA's unique design enables its application across multilingual discourses, as it focuses on uncovering relationships between nodes, making it a versatile tool for global analysis in diverse linguistic contexts. The ability of MTNSA to blend nodes and emotional contexts into a unified analytical model presents a significant advancement in our understanding of digital communication patterns. It equips researchers, marketers, and policymakers with a robust tool to decode the intricate language of social media, contributing profoundly to our comprehension of how emotions and ideas are expressed and disseminated in the digital realm, thereby opening new frontiers for analysis in the dynamic landscape of social media.