  Social media platforms, particularly Telegram, play a pivotal role in shaping
public perceptions and opinions on global and national issues. Unlike
traditional news media, Telegram allows for the proliferation of user-generated
content with minimal oversight, making it a significant venue for the spread of
controversial and misinformative content. During the COVID-19 pandemic,
Telegram's popularity surged in Singapore, a country with one of the highest
rates of social media use globally. We leverage Singapore-based Telegram data
to analyze information flows within groups focused on COVID-19 and climate
change. Using k-means clustering, we identified distinct user archetypes,
including Skeptic, Engaged Advocate, Observer, and Analyst, each contributing
uniquely to the discourse. We developed a model to classify users into these
clusters (Precision: Climate change: 0.99; COVID-19: 0.95). By identifying
these user archetypes and examining their contributions to information
dissemination, we sought to uncover patterns to inform effective strategies for
combating misinformation and enhancing public discourse on pressing global
issues.
