Abstract:
This study explored the temporal dynamics, public engagement, and sentiment
patterns on social media during three major global protests: The Black Lives Matter
Movement (BLMM), the South African Unrest (SAU), and the Masha Amini Protest
(MAP). By analysing tweet distributions, Google Trends data, and sentiment trends,
it revealed how public interest evolved in response to these socio-political events.
The findings indicated that tweet activity often peaked on the third day of key events,
followed by varied post-peak engagement patterns. For instance, BLMM sustained
prolonged interest and engagement, MAP exhibited intermittent resurgences in public
attention, while SAU experienced a sharper decline after its initial peak. Sentiment
analysis revealed unique emotional responses across these movements. BLMM
maintained predominantly positive sentiment, with peaks during significant events
and anniversaries. In contrast, SAU displayed a volatile sentiment landscape, with
sharp drops into negativity followed by recovery phases. MAP demonstrated relative
stability but also saw notable sentiment fluctuations, with critical moments evoking
both positive and negative emotions. These insights underscored the diversity in
public emotional engagement across different socio-political contexts. The study also
examined the synchronization between social media activity and traditional news
coverage, showing that social platforms often acted as early indicators of public
interest, amplifying discourse before mainstream media responded. This highlighted
the role of social media as both a reflection and a driver of public discourse during
socio-political movements. Furthermore, the research introduced archetypes for
social media protests by analysing tweet volumes and sentiment distributions. Using
LOESS smoothing techniques, it proposed generalized models to predict and
understand the dynamics of future protest events in the digital space. These
archetypes enhanced the ability to analyse, compare, and anticipate patterns of online
activism, offering valuable insights into the evolving influence of social media on
public opinion and mobilization. To refine these findings, the study suggested
incorporating advanced time-series analyses and region-specific datasets to validate
and expand the proposed archetypes, providing a more localized perspective on
global protest dynamics.
