Activism via attention: interpretable spatiotemporal learning to forecast protest activities
Abstract The diffusion of new information and communication technologies—social media in particular—has played a key role in social and political activism in recent decades. In this paper, we propose a theory-motivated, spatiotemporal learning approach, ActAttn, that leverages social movement theori...
Main Authors: | Ali Mert Ertugrul, Yu-Ru Lin, Wen-Ting Chung, Muheng Yan, Ang Li |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2019-02-01
|
Series: | EPJ Data Science |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1140/epjds/s13688-019-0183-y |
Similar Items
-
Migrant Labour in China: A Case Study of Labour Discontent, Unrest and Protests
by: Manganelly Sumesh
Published: (2020-05-01) -
The protests in Zhanaozen and the Kazakh oil sector: Conflicting interests in a rentier state
by: Dossym Satpayev, et al.
Published: (2015-07-01) -
Depends on how you count them: the value of general propensity choropleth maps for visualising databases of protest incidents
by: Martin Bekker
Published: (2023-12-01) -
Unrest in Kazakhstan: Economic background and causes
by: Bulat Mukhamediyev, et al.
Published: (2023-10-01) -
Reflection of the style of socio-political symbolism in the poetry of the poets of the forties and the statues and symbols of the Constitutional House of Tabriz
by: Zohreh MortezazadehToori, et al.
Published: (2022-05-01)