Applying Text Mining to Protest Stories as Voice against Media Censorship
Social and Information Networks
2019-01-01 v1 Computers and Society
Abstract
Data driven activism attempts to collect, analyze and visualize data to foster social change. However, during media censorship it is often impossible to collect such data. Here we demonstrate that data from personal stories can also help us to gain insights about protests and activism which can work as a voice for the activists. We analyze protest story data by extracting location network from the stories and perform emotion mining to get insight about the protest.
Keywords
Cite
@article{arxiv.1812.11430,
title = {Applying Text Mining to Protest Stories as Voice against Media Censorship},
author = {Tahsin Mayeesha and Zareen Tasneem and Jasmine Jones and Nova Ahmed},
journal= {arXiv preprint arXiv:1812.11430},
year = {2019}
}
Comments
4 pages, 6 figures, CSCW 2018 : Solidarity Across Borders Workshop. Link : https://cscwsolidarity.wordpress.com/participants/