Abstract: Since the shooting of Black teenager Michael Brown by White police officer Darren Wison 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, we study how these protests and counter-protests diverge by quantifying aspects of their discourse. In particular, we introduce methodology that not only quantifies these divergences, but also reveals whether they are from widespread discussion or a few popular retweets within these groups. We find that #BlackLivesMatter exhibits many informationally rich conversations, while those within #AllLivesMatter are more muted and susceptible to hijacking. We also show that the discussion within #BlackLivesMatter is more likely to center around the deaths of Black Americans, while that of #AllLivesMatter is more likely to sympathize with the lives of police officers and express politically conservative views.