Analyzing social media discourse reveals emotional and content differences in Ethiopian and US perspectives, indicating diverse needs.
Analyzing topics and emotions in social media activism offers valuable insights into the competing voices that shape digital discourse. However, existing research has largely neglected the influence of geographic and linguistic diversity on public dialogue during crises. To address this gap, it is essential to recognize the varied perspectives of local communities and language groups. Doing so helps uncover specific local needs, ensures more inclusive representation, and supports the development of solutions that are responsive to the local context. We leverage machine learning models to analyze 1,036,111 public tweets from the #NoMore movement, including tweets containing #NoMore, #EthiopiaPrevails, and #SayNoMore. Our analysis examined the differences in content, emotional responses, and user influence by comparing tweets from Ethiopia and the United States (US), as well as those written in English and Amharic. The findings reveal distinct societal perspectives, emotional expressions, and opinion dynamics. Ethiopian users emphasized local issues with higher fear and joy responses, while users from the US leaned toward peace-related themes with spikes in anger. Amharic tweets focused on domestic concerns with greater emotional intensity than English tweets. These insights help surface region and language-specific perspectives often marginalized in mainstream coverage, paving the way for more inclusive and effective approaches to societal challenges.
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Zeleke et al. (2026) studied this question.
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