Activism today is no longer bound to be organization-led, but has evolved to be mostly crowd-enabled connective actions via social media where much of the coordination and mobilization take place. This poses a challenge for social movement researchers to even keep track of the full set of action repertoires. In the social movement in Hong Kong in 2019, protesters have relied on Telegram, an encrypted messaging service, and other digital channels to mobilize thousands of collective actions of various scales and disseminate real-time updates on police’s anti-riot measures such as the use of tear gas. The months-long conflicts and the lack of official statistics render conventional manual data collection approaches difficult to implement. Using text-mining techniques, we extracted spatial–temporal information of the protesters’ call for actions and the police’s tear gas use in the social movement from over 12,000 messages collected from more than 100 Telegram channels operated by the activists and news media. The validation shows that the resulting datasets are more inclusive, especially small-scale actions, than manually compiled ones. Using the data, we identify a pattern of hybridized mobilization between organizational and non-organizational activists in the Anti-ELAB movement. This paper demonstrates how utilizing social media data can complement existing data collection methods and build a more-comprehensive record of collective actions with greater potential in supporting social movement research in the age of digitization.
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Data are released on the project website: https://antielabdata.jmsc.hku.hk
Lennon Wall (liannongqiang 連儂牆) is a makeshift bulletin board-like space that allows anyone to put up protest-related propaganda materials.
Human chain is an event where participants hold hands to form a chain of humans spanning across streets and neighborhoods.
We decide to adopt a stricter standard of media here for a more credible cross-evaluation later on. Only channels that are operated by the traditional news media agencies, such as television stations and newspapers, were included. Internet-based media and citizen reporting were excluded.
Precisely speaking, it stretches across five metro stations. Without an authoritative definition of neighborhoods, the surrounding of a metro station is often seen as a neighborhood in Hong Kong.
We adapted the geodesic algorithm by C. F. F. Karney (https://dx.doi.org/10.1007/s00190-012-0578-z) provided in the R package geosphere.
The figures can be downloaded from https://figshare.com/articles/ANTIELAB_social_movement_statistics/12228032
We define accessible on foot as whether one can walk from one district to another under reasonable and normal circumstances. For example, while it is possible to walk from Wong Tai Sin District to Sha Tin District, they are not regarded as accessible on foot since the journey involves hiking across a mountain.
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This study is supported by the Faculty of Social Sciences, The University of Hong Kong.
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Open data access: https://antielabdata.jmsc.hku.hk/data/
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Teo, E., Fu, Kw. A novel systematic approach of constructing protests repertoires from social media: comparing the roles of organizational and non-organizational actors in social movement. J Comput Soc Sc 4, 787–812 (2021). https://doi.org/10.1007/s42001-021-00101-3
- Social media
- Event extraction
- Location extraction
- Social movement
- Connective action