In this study, we relied on computational methods to answer 5 research questions: RQ1: What were the dynamics of Hong Kong protest movement’s development on Telegram? RQ2: How fragmented was the citation network of public Telegram channels and groups related to the Hong Kong protest movement of 2019? RQ3: Which topics were discussed by political activists on Telegram in relation to the Hong Kong’s protests of 2019? RQ4: What are the dynamics of leadership in Telegram-based activities during the 2019 Hong Kong protests? RQ5: Did the enactment of the Security Law affect the activities of Hong Kong’s political Telegramsphere? We relied on the data collected from Telegram (see the underlying dataset and accompanying documents), and, to answer RQ1, 2 and 4, relied on network analysis techniques (e.g., community detection) and network analytic metrics (e.g., modularity scores). To answer RQ3, we employed computational text analysis. To answer RQ5, we used Interrupted Time Series Analysis. Further details on the metrics used are openly available in the linked preprint https://osf.io/preprints/socarxiv/ueds4/.