What Truly Matters? Using Linguistic Cues for Analyzing the #BlackLivesMatter Movement and its Counter Protests: 2013 to 2020
Jamell Dacon, Jiliang Tang

TL;DR
This study analyzes social media linguistic cues from 2013 to 2020 to understand how different movements like Black Lives Matter and counter protests use language and hashtags, revealing biases and thematic focuses.
Contribution
It introduces a multi-level text analysis of nearly 37 million tweets to uncover linguistic patterns and thematic relationships in social activism movements over time.
Findings
Black Lives Matter tweets focus on police brutality and racial injustice.
Counter protests use racially prejudicial hashtags more frequently.
Movements like Blue Lives Matter and All Lives Matter show different thematic focuses.
Abstract
Since the fatal shooting of 17-year old Black teenager Trayvon Martin in February 2012 by a White neighborhood watchman, George Zimmerman in Sanford, Florida, there has been a significant increase in digital activism addressing police-brutality related and racially-motivated incidents in the United States. In this work, we administer an innovative study of digital activism by exploiting social media as an authoritative tool to examine and analyze the linguistic cues and thematic relationships in these three mediums. We conduct a multi-level text analysis on 36,984,559 tweets to investigate users' behaviors to examine the language used and understand the impact of digital activism on social media within each social movement on a sentence-level, word-level, and topic-level. Our results show that excessive use of racially-related or prejudicial hashtags were used by the counter protests…
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Taxonomy
TopicsSocial Media and Politics · Hate Speech and Cyberbullying Detection · Media Influence and Politics
