Twitter Analysis:
#BackLivesMatter & #StopAsianHate

What are People Talking about in #BackLivesMatter and #StopAsianHate?: Exploring and Categorizing Twitter Topics Emerged in Online Social Movements through the Latent Dirichlet Allocation Model

Black Lives Matter (BLM) and Stop Asian Hate (SAH) are two social movements that have spread on Twitter that promote protests and activities against racism and increase the public’s awareness of other social challenges that minority groups face. Very few research explored BLM and SAH’s Twitter topics in a rigorous quantified and data-centered approach. Therefore, in this research, we adopted a mixed-method approach to comprehensively analyze BLM and SAH Twitter topics.

Research Question

RQ1: What are the main topics being discussed in tweets with #BlackLivesMatterblacklivesmatter and #StopAsianHatestopasianhate hashtags?

RQ2: What are the connections between the #BlackLivesMatterblacklivesmatter and #StopAsianHatestopasianhate social movements on Twitter and the related offline social movements/events?

RQ3: What are the differences and similarities in the topics that emerged in the online movements using these two hashtags?

Method

To answer these RQs, we collected 1,263,683 tweets with the #BlackLivesMatter hashtag from May to December 2020 and 96,691 tweets with the #StopAsianHate hashtag from March to December 2021.

We implemented:

(1) The latent Dirichlet allocation (LDA) model to understand the top high-level words and topics.

(2) Open-coding analysis to identify specific themes across the tweets.

Findings

Both quantitative and qualitative findings show that online social movements on Twitter and offline events in both movements reinforce one another. We anticipated that the disparity between the topics in the two movements stems from these movements’ differing origins. Discussions in the SAH movement cover a broader range of topics than the BLM movement. Further investigation is required to uncover the underlying reasons for the difference in topics between the BLM and SAH movements.

Our study contributes to the topic analysis of social movements on social media platforms in particular and the literature on the interplay of AI, ethics, and society in general.