TY - GEN
T1 - User Archetypes and Information Dynamics on Telegram
T2 - 34th ACM Web Conference, WWW Companion 2025
AU - Ligo, Val Alvern Cueco
AU - Yin Cheung, Lam
AU - Lee, Roy Ka Wei
AU - Saha, Koustuv
AU - Tandoc, Edson C.
AU - Kumar, Navin
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.
PY - 2025/5/23
Y1 - 2025/5/23
N2 - 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, such as Strategic Disruptor, Empirical Enthusiast, Inquisitive Moderate, and Critical Examiner, 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).
AB - 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, such as Strategic Disruptor, Empirical Enthusiast, Inquisitive Moderate, and Critical Examiner, 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).
KW - Information flow
KW - Misinformation
KW - Singapore
KW - Telegram
UR - https://www.scopus.com/pages/publications/105009245125
UR - https://www.scopus.com/pages/publications/105009245125#tab=citedBy
U2 - 10.1145/3701716.3717542
DO - 10.1145/3701716.3717542
M3 - Conference contribution
AN - SCOPUS:105009245125
T3 - WWW Companion 2025 - Companion Proceedings of the ACM Web Conference 2025
SP - 2685
EP - 2688
BT - WWW Companion 2025 - Companion Proceedings of the ACM Web Conference 2025
PB - Association for Computing Machinery
Y2 - 28 April 2025 through 2 May 2025
ER -