Statistical Hypothesis Testing and Modelling of Peoples’ Power: A Causal Study of the #BlackLivesMatter Movement via Hawkes Processes on Social and Mass Media

In the current mass media landscape with a few corporate owners and operating under the propaganda model of communication aimed at manufacturing system-supportive consent, and the algorithmic-rent seeking business models of most popular social media platforms, we set out to ask whether Peoples still have power to take collective real-world action that may be counter to prevailing media tendencies. We study interactions in social media and the reports in mass media during the Black Lives Matter (BLM) protests following the death of George Floyd. We implement open-source pipelines to process the data at scale and employ the self-exciting counting process known as Hawkes process to address our main question: is there a causal relation between interactions in social media and reports of street protests in mass media? Specifically, we use network models to identify such interactions in Twitter, that supported the BLM movement, and compared the timing of these interaction to those of news reports of street protests mentioning George Floyd, via the Global Database of Events, Language, and Tone (GDELT) Project. The comparison was made through a Bivariate Hawkes process model for a formal hypothesis test of Granger-causality. We show that interactions in social media that supported the BLM movement, at the beginning of nationwide protests, caused the global mass media reports of street protests in solidarity with the movement. We also use more general Hawkes process model to understand the diffusion of specific influential messages in social media. Our study suggests that BLM activists have harnessed social media to mobilise street protests across the planet despite the concentrated ownership of mass media and the algorithmic rent-seeking business models of social media platforms.