Paper Info
Title
On predicting social unrest using social media.
Abstract
We study the possibility of predicting a social protest (planned, or unplanned) based on social media messaging. We consider the process called mobilization, described in the literature as the precursor of participation. Mobilization includes four stages: being sympathetic to the cause, being aware of the movement, motivation to take part and ability to participate. We suggest that expressions of mobilization in communications of individuals may be used to predict the approaching protest. We have utilized several Natural Language Processing techniques to create a methodology to identify mobilization in social media communication. Results of experimentation with Twitter data collected before and during the 2015 Baltimore events and the information on actual protests taken from news media show a correlation over time between volume of Twitter communications related to mobilization and occurrences of protest at certain geographical locations. We conclude with discussion of possible theoretical explanations and practical applications of these results.
Year
DOI
Venue
2016
10.5555/3192424.3192441
ASONAM '16: Advances in Social Networks Analysis and Mining 2016 Davis California August, 2016
Keywords
Field
DocType
social unrest,social media messaging,mobilization,natural language processing techniques,social media communication,Twitter communications,geographical locations
Mobilization,Data mining,Social media,Sociology,News media,Network completion,Unrest
Conference
ISBN
Citations 
PageRank 
978-1-5090-2846-7
6
0.51
References 
Authors
14
10
Name
Order
Citations
PageRank
Rostyslav Korolov1201.80
Di Lu24114.62
Jingjing Wang3555.28
Guangyu Zhou4451.63
Claire Bonial523218.02
Clare R. Voss634429.51
Lance M. Kaplan776981.55
William A. Wallace8314.64
Jiawei Han9430853824.48
Heng Ji101544127.27