This thesis employs a computational linguistic methodology to investigate the framing of echo chambers on Twitter, using similarity and difference over time as a proxy. The analysis centers on the 2023 Chinese Balloon Incident, which involved the U.S. military shooting down a Chinese balloon, and examines coalescence or divergence in discourse using string similarity comparisons, sentiment scores, topic modeling, word embedding, and top terms. The thesis aims to problematize existing methodologies and instead focuses on everyday language use to better observe political and social agency in technologized spaces. Through this approach, the study contributes to a deeper understanding of the impact of social media on democratic discourse and the broader political landscape.