Paper detail

#EndSARS Protest: Discourse and Mobilisation on Twitter

Using the @NGRPresident Twitter handle, the Government of Nigeria issued a special directive banning Special Anti-Robbery Squad (SARS) with immediate effect. The SARS is a special police unit under the Nigeria Police Force tasked with the responsibility of fighting violent crimes. However, the unit has been accused of waves of human rights abuse across the nation. According to a report by Amnesty International, between January 2017 and May 2020, 82 cases of police brutality have been committed. This has led to one of the major protests demanding more measures to be taken. The #EndSARS hashtag was widely used by the protesters to amplify their messages and reach out to wider communities on Twitter. In this study, we present a critical analysis of how the online protest unfolded. Essentially, we examine how the protest evolves on Twitter, the nature of engagement with the protest themes, the factors influencing the protest and public perceptions about the online movement. We found that the mobilisation strategies include direct and indirect engagements with influential users, sharing direct stories and vicarious experiences. Also, there is evidence that suggests the deployment of automated accounts to promote the course of the protest. In terms of participation, over 70% of the protest is confined within a few states in Nigeria, and the diaspora communities also lent their voices to the movement. The most active users are not those with high followership, and the majority of the protesters utilised mobile devices, accounting for 88% to mobilise and report on the protest. We also examined how social media users interact with the movement and the response from the wider online communities. Needless to say, the themes in the online discourse are mostly about #EndSARS and vicarious experiences with the police, however, there are topics around police reform and demand for regime change.

preprint2023arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.