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PLoS One. 2018 Apr 18;13(4):e0195644. doi: 10.1371/journal.pone.0195644. eCollection 2018.

Divergent discourse between protests and counter-protests: #BlackLivesMatter and #AllLivesMatter.

Gallagher RJ1,2,3, Reagan AJ1,2,3, Danforth CM1,2,3, Dodds PS1,2,3.

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Department of Mathematics and Statistics, University of Vermont, Burlington, VT, United States of America.
Computational Story Lab, Vermont Complex Systems Center, University of Vermont, Burlington, VT, United States of America.
Vermont Advanced Computing Core, University of Vermont, Burlington, VT, United States of America.


Since the shooting of Black teenager Michael Brown by White police officer Darren Wilson in Ferguson, Missouri, the protest hashtag #BlackLivesMatter has amplified critiques of extrajudicial killings of Black Americans. In response to #BlackLivesMatter, other Twitter users have adopted #AllLivesMatter, a counter-protest hashtag whose content argues that equal attention should be given to all lives regardless of race. Through a multi-level analysis of over 860,000 tweets, we study how these protests and counter-protests diverge by quantifying aspects of their discourse. We find that #AllLivesMatter facilitates opposition between #BlackLivesMatter and hashtags such as #PoliceLivesMatter and #BlueLivesMatter in such a way that historically echoes the tension between Black protesters and law enforcement. In addition, we show that a significant portion of #AllLivesMatter use stems from hijacking by #BlackLivesMatter advocates. Beyond simply injecting #AllLivesMatter with #BlackLivesMatter content, these hijackers use the hashtag to directly confront the counter-protest notion of "All lives matter." Our findings suggest that Black Lives Matter movement was able to grow, exhibit diverse conversations, and avoid derailment on social media by making discussion of counter-protest opinions a central topic of #AllLivesMatter, rather than the movement itself.

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