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

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posted on 2023-02-24, 08:54 authored by King Wa FuKing Wa Fu

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.


There are altogether four csv files for each type respectively: totalm_df.csv, mobnet_df.csv, coordnet_df.csv, and pafnet_df.csv. 


You can read the files by using the following source code in R:


require(readr)

require(igraph)

totalm.grp <- graph_from_data_frame(read_csv("totalm_df.csv"))

mobnet.grp <- graph_from_data_frame(read_csv("mobnet_df.csv"))

coonet.grp <- graph_from_data_frame(read_csv("coordnet_df.csv"))

pafnet.grp <- graph_from_data_frame(read_csv("pafnet_df.csv"))


# from_type & to_type: Channel types

# A (Self-organized), M (Media), O (Others), and P (Politicians)


To cite: Fu, KW. (2023). Digital mobilization via attention building: The logic of cross-boundary actions in the 2019 Hong Kong social movement. The Information Society, 1-13. doi:10.1080/01972243.2023.2185717


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