Data in the paper "Digital mobilization via attention building: The logic of cross-boundary actions in the 2019 Hong Kong social movement"

This study scrutinizes the mechanism of online activism in an analysis of 2 million Telegram Channel messages collected during the 2019 Hong Kong Anti-Extradition Law Amendment Bill movement. It classifies the Telegram's action repertioires networks as four types: total messages, mobilization, tactical coordination, and personal action framing. <br> There are altogether four csv files for each type respectively: totalm_df.csv, mobnet_df.csv, coordnet_df.csv, and pafnet_df.csv. <br> You can read the files by using the following source code in R: <br> require(readr) require(igraph) totalm.grp &lt;- graph_from_data_frame(read_csv("totalm_df.csv")) mobnet.grp &lt;- graph_from_data_frame(read_csv("mobnet_df.csv")) coonet.grp &lt;- graph_from_data_frame(read_csv("coordnet_df.csv")) pafnet.grp &lt;- graph_from_data_frame(read_csv("pafnet_df.csv")) <br> # from_type &amp; to_type: Channel types # A (Self-organized), M (Media), O (Others), and P (Politicians) <br> To cite: Fu, KW. (2023). Digital mobilization via attention building: The logic of cross-boundary actions in the 2019 Hong Kong social movement. <em>The Information Society</em>, 1-13. doi:10.1080/01972243.2023.2185717 <br>