Activism via attention: interpretable spatiotemporal learning to forecast protest activities

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...

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Bibliographic Details
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:
Interpretable spatiotemporal learning
Event forecasting
Civil unrest
Protest activities
Online Access:http://link.springer.com/article/10.1140/epjds/s13688-019-0183-y

Internet

http://link.springer.com/article/10.1140/epjds/s13688-019-0183-y

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