Abstract
This teaching case investigates how social media platforms – particularly Twitter – functioned as socio-technical infrastructures for decentralised operational control during the 2020 EndSARS protests in Nigeria. It explores how digital visibility became a coordination resource that substituted for formal institutions. It focuses on how digital platforms, particularly Twitter, functioned as live information systems for facilitating volunteer-led supply chain operations, donor transparency, and crowd-sourced accountability in the absence of formal leadership or infrastructure. The case analyses how Twitter became a form of operational power, with every update functioning as both coordination mechanism and public proof. It also explores the risks of misinformation, information overload, and coordination breakdowns in high-velocity, emotionally charged environments. Students will critically evaluate how digital tools shape coordination in informal crisis response settings, assess the operational trade-offs between speed and accuracy, and apply systems thinking to examine feedback loops, agile decision-making, and communication overload. The case encourages reflection on how information systems perform in contexts of uncertainty, trust-based collaboration, and public scrutiny. The central problem addressed is how real-time, trust-based coordination can occur in open digital environments where accuracy, overload, and credibility continuously compete.
By engaging with this case, students will be able to: 1. Analyse the role of digital platforms as coordination technologies in informal, decentralised operations, using Twitter and other tools as examples of real-time information systems in action. 2. Evaluate the trade-offs between speed, accuracy, and visibility in IT-enabled logistics and crisis response, with reference to agile project management, digital trust, and participatory accountability. 3. Apply systems thinking to identify how feedback loops, signal-to-noise ratios, and information flows shape responsiveness, risk, and operational resilience in live, high-velocity environments. 4. Assess the operational and ethical implications of transparency, including its role in enabling accountability and trust, as well as its risks for misinformation, reputational harm, and burnout in digitally mediated operations. 5. Design or critique digital coordination practices for informal or crisis contexts, drawing on lessons from real-time data use, unstructured communication systems, and the emergence of informal authority through credibility and digital visibility.Learning outcomes
Introduction: The EndSARS protests
In conventional crisis logistics, command flows through hierarchy, data through verified systems, and action through defined procedures. During the 2020 EndSARS protests, none of these existed. Protesters faced an operational puzzle: How can dispersed volunteers coordinate logistics and information in real time without formal leadership or stable infrastructure? This question anchors the case as an exploration of technology-enabled coordination under institutional failure.
The EndSARS protests erupted in October 2020 after years of anger at police brutality. What began as a hashtag became a nationwide mobilisation of young Nigerians using phones, spreadsheets, and live streams to substitute for absent state infrastructure. Crowd-sourced logistics replaced command chains; visibility became organisation.
The movement operated like a system – one designed in motion. Twitter became the meeting ground. WhatsApp groups became delivery routes. Google Sheets became records. Voice notes replaced boardroom briefings. In the absence of a formal structure, a functional one emerged. With it came an insistence: that young Nigerians could not only imagine a different country, but organise around it. What they demanded was simple – an end to police brutality, justice for the dead, and a say in the structures that governed them. What they built was more complex: an informal but operational supply chain of action, care, and accountability.
In that period, the line between protest and project blurred. Every hand raised to protest was also used to build. It was in this context that people like Tayo found themselves drawn into roles they never trained for – coordinators, dispatchers, record-keepers, analysts. What happened next is part of Nigeria’s political memory. But what happened during – beneath the headlines and away from the cameras – was a story of improvisation, digital coordination, and shared responsibility. This case follows one thread in that story, through the experience of Tayo, a tech analyst who joined the protest infrastructure from behind a screen and helped keep things moving when movement itself became a kind of resistance.
Within this emergent system, individuals like Tayo, a data analyst, became accidental operations managers. By converting tweets into Google Sheets and creating a public form for donations, he helped transform unstructured social data into traceable workflows. His experience illustrates the transition from user to system node: a citizen leveraging everyday digital tools to build temporary but functional infrastructure for logistics and accountability.
Digital platforms as informal information systems
Long before the protests began, young Nigerians had been using digital platforms to express frustration and organise their lives around a system that often refused to recognise them. As information-systems scholars note (Alter, 2002; Starbird, 2014), this represents socio-technical adaptation – the repurposing of everyday communication tools into coordination infrastructure when formal systems fail. In a context where public infrastructure was unreliable, and institutional trust was fragile, platforms like Twitter and WhatsApp took on more than a social function – they became the de facto architecture for coordination, problem-solving, and response. These platforms were not designed to replace government systems or civic institutions, but in the absence of timely information, clear policies, and consistent support, they were adapted – repeatedly and creatively – into systems that filled critical gaps (Figure 1). Flow of information and action in the EndSARS network.
This flow diagram clarifies how social media interactions became a live operations loop.
During the EndSARS protests, this adaptation became visible in real time. Twitter threads became dispatch boards; hashtags became noticeboards for missing persons, legal advice, donation links, and safety alerts. Timelines were updated faster than any official communication, often drawing on a network of anonymous contributions, crowd-sourced verification, and digital traceability. No single user was in charge, and yet a kind of loose coordination emerged – held together by shared urgency, responsive moderation, and the informal reputations of credible posters who had, over time, earned the trust of the online community through accuracy, speed, or service.
It would be too simple to describe these platforms as chaotic or reactive. What emerged, instead, was a set of informal information systems – flexible, decentralised, and purpose-built through daily use and collective memory. These systems operated through partial visibility; not everyone could see everything, but those who needed to find each other often did. The logic of these networks was not built on formal roles or organisational charts, but on retweets, timestamps, hashtags, and replies. What mattered was the reliability of the information, the speed with which it travelled, and the action it enabled.
For many involved – like Tayo, whose quiet skills in data organisation found unexpected urgency – the system was both technological and social. A spreadsheet only worked if people trusted the link. A tweet only mattered if it led someone to safety, or support, or shelter. And the information was not neutral; it was always relational, dependent on human effort to verify, relay, and act. Digital platforms, in this moment, became not just a site of protest but a structure of coordination. They blurred the lines between activism and administration, between visibility and action.
These were systems without manuals. They grew through shared trial and error. Mistakes happened – misinformation spread, duplicate efforts clashed, critical requests were missed. But people adapted. They learned to tag relevant accounts, update documents, cross-reference entries, and pass along only what they had confirmed. It was not perfect, but it was real. And for those days in October, it was enough to keep food moving, bail funds flowing, and bodies protected.
What the state could not track, the crowd could trace. What official channels failed to communicate, online networks broadcast with urgency and care. In this sense, the platforms did not just hold the protest – they made its infrastructure visible, functional, and, for a while, sustainable.
From visibility to action: How information moved
Visibility, during the EndSARS protests, was not a goal in itself. Twitter’s affordances – threading, timestamping, and tagging – acted as a coordination layer linking human perception to operational response. It was a mechanism – one that turned observation into obligation, and documentation into direction. Information did not stop at awareness; it travelled toward action, connecting those who witnessed with those who responded. In a country where public institutions often failed to inform, digital platforms became channels through which the crowd could see, understand, and act – all in one motion.
The flow was rarely linear. A single tweet could move in multiple directions – flagged by an observer, verified by a coordinator, relayed to a WhatsApp group, shared in a DM, referenced in a Google Sheet, and finally translated into a real-world decision: send money, send food, call a lawyer, and alert a medic. Information was not simply broadcast; it was handled. Passed along with care, filtered through judgement, and acted on with urgency.
In these moments, speed and reliability had to be held in balance. Visibility without confirmation could be dangerous – amplifying rumours, misplacing resources, exposing people to risk. But delay could cost lives. What emerged was a culture of pragmatic verification: not formal but functional, based on proximity, repetition, and collective discernment. When a piece of information appeared in multiple trusted channels – especially from known accounts, ground-level observers, or organisers – it gained enough credibility to trigger action.
Tayo found himself in the middle of this flow. His spreadsheets began to serve not just as records but as relay points – filtering dozens of reports each hour into summaries that others could scan and act on. He did not need to be everywhere; he needed to notice patterns, update quickly, and make it easier for others to see what mattered. His job was less about conclusions and more about clarity.
Others took different roles in the chain. Some stayed on the ground, feeding updates into shared groups. Others curated threads, translated jargon, and flagged urgent needs. There were people who monitored police movements, people who archived footage, and people who called ahead to hospitals to prepare for incoming cases. Everyone was working with partial information, yet the system kept moving because each node in the network passed something on.
Unlike formal institutions, which rely on chain-of-command and fixed reporting protocols, this network worked because people trusted each other to act. There were no memos, no official briefings, no standard operating procedures. Yet the system moved – faster, often, than any state response. Not because it was flawless, but because it was attentive. Because people did not wait to be asked. They saw, they understood, and they did what they could.
The information that mattered most was not always the loudest. Sometimes it was a quiet tweet from a sibling looking for someone detained. Sometimes it was a message buried in a Telegram chat about a medical supply shortage. But the right person would see it, pull it out, and make sure it moved. Visibility, in that sense, was never the end point. It was the first step in a chain reaction – one that turned attention into action, and observation into care.
The section demonstrates how digital visibility, often dismissed as noise, can evolve into a form of operational control when paired with collective trust.
Designing for trust and traceability
In a context of weak public institutions, traceability became a substitute for bureaucratic accountability. Credibility, earned through consistent digital behaviour, operated as governance. It had to be earned, signalled, and sustained through patterns of credibility, consistency, and responsiveness. Over time, this gave rise to a quiet but effective hierarchy – one not based on title or institution, but on traceability and track record.
Certain names began to stand out, not because they were famous, but because they were dependable. An account that regularly shared verified bail information. A handle that posted donation receipts without delay. A voice note that calmly summarised needs without exaggeration. These actors formed an informal layer of credibility, recognised not by formal badges but by how their information moved-quickly, widely, and with minimal correction.
Twitter affordances and operational functions.
These affordances collectively created a traceable, trust-based system of ‘soft governance’, where accountability emerged from visibility rather than authority.
This participatory verification was not always neat. It relied on social memory, repeated engagement, and sometimes instinct, but it worked. People asked questions before forwarding messages. Screenshots were dated. Duplicate donation requests were flagged. There was a quiet diligence running beneath the surface of protest logistics – not because people feared error, but because they understood what depended on getting it right.
The act of tracking data – donations, deliveries, arrests, and disbursements – was not only administrative. It was political. It allowed people to hold each other accountable without resorting to blame. If a food order did not arrive, the spreadsheet could show where it stopped. If a bail fund was delayed, the ledger could reflect when the request came in. These systems offered structure without control, coordination without coercion. They enabled people to act not just on belief, but on information that could be traced, checked, and passed on with confidence.
Tayo contributed to this governance. He timestamped every entry in his sheets, colour-coded verification status, and updated response logs with short notes – ‘confirmed by DM’, ‘pending delivery’, ‘awaiting phone call’. No one told him to do this. But over time, others mirrored his habits, copied his templates, and folded his updates into broader systems. His work became legible because it was careful. And in a space where visibility could be dangerous, traceability was a safer way to be trusted.
This trust-based system of traceable, shared verification was not perfect. But for the duration of the movement, it did what few public systems in the country had managed to do consistently: it earned the confidence of the people it served, not through power, but through practice.
Managing flow and noise
The key operational bottleneck was not scarcity of data but its velocity and volume. Information arrived faster than it could be validated – illustrating the information-processing limits described by Galbraith (1974). Amidst the noise, some things got through. Supplies were delivered. Legal support arrived. Protesters were moved out of danger. The system worked – not because the volume was manageable, but because the flow was shaped.
Managing that flow became a task in itself. It was not enough to know what was happening; someone had to decide what to act on, what to archive, what to flag, and what to wait on. The most effective participants were not just those who amplified – they were those who filtered. They read everything so others would not have to. They reworded for clarity, stripped messages of excess emotion where it risked confusion, and grouped needs by location, urgency, or type.
This filtering was or care rather than censorship. Every update was someone’s reality, but not every update needed to be forwarded. In the absence of a gatekeeping body, individuals assumed the role of curators – sorting through hundreds of inputs to ensure that the right message reached the right person at the right time. In a digital space already shaped by viral logic, this kind of filtering worked against the grain, slowing down noise to make space for what mattered.
Volunteers developed informal data-management protocols – filtering, tagging, and cross-checking – to regain signal-to-noise balance. Organisation tools became crucial: Twitter lists, pinned threads, shared folders, numbering systems, and colour-coded tabs. These were not just technical choices; they were methods of keeping the system human. With volume came fatigue, and without structure, critical needs could vanish into the stream. Lists were updated hourly. Summaries were posted at regular intervals. When misinformation appeared, it was responded to – not just with correction, but with better information, better labelled, better sourced.
Tayo felt this acutely. He spent much of his time not entering new data, but maintaining what was already there – cleaning duplicates, marking completed tasks, and highlighting neglected ones. He became someone others tagged when they were not sure where a request fit. His role was to help the system breathe to keep it from choking on its own volume.
Prioritisation became a survival skill. Some messages were urgent because lives were at stake. Others were urgent because confusion could spread quickly if left unattended. And others were held, quietly, because the moment was not right. People learned to watch patterns: spikes in location-based tweets, sudden drops in donation levels, changes in police movement. These signals did not appear in a command centre – they emerged through observation and shared memory.
In a space where everything felt urgent, the work was in knowing what could wait. That judgement was not always perfect, but it kept the system from fracturing. The result was a kind of quiet order that was not imposed but assembled. An order that made room for chaos but did not let it lead.
Agile coordination in a distributed network
Participants never labelled their methods ‘agile’, yet the system’s logic mirrored agile principles: iteration, decentralisation, and continuous adaptation. The movement’s strength ay in its ability to respond, adjust, and improve under pressure. What emerged across the protest networks was solidarity and a distributed system of problem-solving. Each node made decisions, adapted in real time, and shared what worked. It was, in effect, agile without a roadmap.
Agile practices observed in the EndSARS coordination network.
The network exemplified agility as mindset, not method – functioning through trust and iteration rather than control or planning documents.
Responsiveness was about speed and fit. Solutions were designed for specific problems, in specific places, at specific moments. If one protest site needed crutches and another needed torchlights, they were treated differently. If police began using tear gas in one city and live rounds in another, the messaging changed. Action plans were not rolled out-they were built on the spot, based on real-time updates, local input, and available resources. The goal was never perfection. It was function.
Decision-making was decentralised by necessity. There was no command centre and no designated lead. Instead, initiative passed freely between people and places. Someone who handled legal support in Abuja might never speak to the person handling logistics in Ibadan. But each was trusted to make the right call in their context, and systems emerged to connect their work when needed. This was not the absence of coordination – it was a different kind of coordination, shaped by autonomy, mutual awareness, and shared purpose.
The system grew through feedback loops, rather than forecasts. When something failed – when food ran out, or information was outdated – it was corrected quickly. Mistakes weren’t hidden; they were discussed, flagged, redesigned. In a traditional structure, failure often moves up the chain. Here, it moved across – into new tools, better formats, faster responses. Change did not have to be approved. It only had to be useful.
For Tayo, this system became familiar. He did not know what role he would have each day until he logged on. Some mornings, he filtered legal cases. By evening, he was checking supply logs. When a tool stopped working, he built another. When someone else’s sheet was better, he retired his own. He did not call this agile work. He called it ‘figuring things out’. But the principles held: short feedback cycles, continuous improvement, user-centred design, and trust-based delegation.
The coordination model that held the protests together was not scalable in the traditional sense, but it was sustainable while it lasted – because it was light, flexible, and deeply human. It recognised that in crisis, the best systems are those that can shift without breaking, and that decision-making is most powerful when shared.
Twitter as a coordination layer
From an information-systems perspective, Twitter operated as the integration layer connecting various tools (WhatsApp, Google Sheets, Telegram) into a single, user-managed coordination environment.
While many platforms played a role during the EndSARS protests, Twitter occupied a distinct position – not just as a site for visibility or advocacy, but as an operational layer for coordination. It offered more than reach; it offered structure. Through its specific features – threading, timestamping, tagging, and searchability – Twitter enabled the real-time circulation, categorisation, and tracking of information in a way that made large-scale, decentralised action possible.
Threading allowed for continuity. Rather than scattering updates across isolated posts, organisers and contributors used threads to build running commentaries – on legal aid, protest locations, medical needs, bail status, or donation disbursement. These threads acted as living documents, updated incrementally and accessible at a glance. For users joining midstream, threads offered context. For those already involved, they offered a place to return, refresh, and repost. In a rapidly moving situation, this continuity became a form of stability.
Timestamping, though subtle, played a critical role in operational trust. The ability to see exactly when a post was made helped users assess whether the information was current, outdated, or already resolved. In a space where misinformation could spread quickly and conditions changed by the hour, timestamps became part of how people evaluated urgency and reliability. They provided a temporal anchor for each request, warning, or update – making it easier to organise responses in sequence.
Tagging enabled targeted coordination. Protesters and organisers created tags not just for slogans – #EndSARS, #LekkiMassacre – but for roles, resources, and cities: #LegalAidAbuja, #MedicalTeamPH, #DonateToSurvivors. These were not just symbolic labels; they were routing tools. When someone needed to connect with a lawyer in Ibadan or a nurse in Surulere, tagging allowed the platform to function like a switchboard –linking people across geography, interest, and need.
Searchability gave Twitter a memory. Unlike WhatsApp or Telegram, where information could be buried in volume, Twitter’s search function allowed users to find past updates, verify claims, and trace developments. Whether looking for a past receipt, a list of arrested protesters, or the last known location of an ambulance, users relied on the ability to query the public archive. Hashtags, handles, and phrases became part of a shared taxonomy – ways of indexing the movement’s actions and artefacts.
Crucially, these affordances were not used in isolation. They were combined, layered, and adapted in real time. A tweet might be timestamped, threaded, tagged, and embedded with links to external forms or documents. The result was a platform that functioned – informally but effectively – as a live dashboard: part megaphone, part logbook, part command centre.
Tayo relied on this layer constantly. Twitter was where he found updates, shared summaries, confirmed reports, and received questions. It was where he watched new needs emerge and old ones close. He used it to trace supply chains, check delivery confirmations, and build trust with users he never met. The platform gave him no authority, but it gave him access-access to people, to tasks, to information that moved.
Twitter, in this context, was a structure, a digital infrastructure that helped a movement without offices or titles to stay visible, coordinated, and responsive under pressure.
What remains
The protests ended in late October 2020 following the Lekki Toll Gate shootings. When the networks quieted, what remained was the memory of a crowd that built operational order out of digital fragments – a brief substitution of civic technology for absent institutions.
What lingered, in the days and weeks that followed, was not only grief or fatigue, but memory. Memory of how it felt to be part of something that worked – not perfectly, not permanently, but with purpose. Memory of how strangers coordinated without titles. Of how food arrived where it was needed. Of how lawyers showed up without being called by name. These were not systems built for longevity, but they held long enough to show what was possible.
Tayo did not save copies of everything. Some links expired. Some records were deleted out of caution. But the logic of the work stayed with him. The quiet discipline of tracking what mattered. The habit of checking timestamps. The instinct to build only what someone else could use. He returned to his regular job eventually, but not untouched. Coordination now meant something different to him. Less about structure, more about care.
For many involved, what remained was not an organisation or platform, but a way of working – a way of responding to each other in real time, under pressure, without waiting. The energy of the movement could not be preserved whole. But fragments remained: practices, relationships, habits of attention. A mental map of who to call. A better spreadsheet template. A deeper sense of what it meant to show up.
The digital systems dissolved, but the experience of using them – of improvising, adjusting, listening – left an imprint. Not all of it was good. Some people burned out. Some were afraid. Some walked away altogether. But those who stayed carried something with them: a quiet knowledge that when the formal world stalled, people made another one-out of code, kindness, and coordination.
What remains is not the platform or the protest. It is the understanding that systems do not need to be perfect to be possible. That tools do not need to be custom-built to be useful. And that trust, once practised at scale, becomes a kind of infrastructure too.
The case ultimately reveals that information systems can arise organically when social trust meets digital infrastructure. It invites students to view coordination not as a by-product of technology but as a human design problem occurring in real time under constraint.
Discussion questions
1. Using Alter’s Work System Framework, analyse how Twitter, WhatsApp, and Google Sheets operated as socio-technical information systems that enabled decentralised coordination. Identify how features such as threading, tagging, and timestamping substituted for formal logistics processes and evaluate their limitations in sustaining reliable operations. 2. Drawing on Bernstein’s (2012) Transparency Paradox, discuss how radical visibility enhanced trust and accountability yet also created risks of misinformation, reputational harm, and volunteer burnout. How might organisations design for strategic, rather than total, transparency? 3. Apply Systems Thinking to map how feedback loops and signal-to-noise ratios shaped coordination quality. Identify informal mechanisms that acted as buffers against overload. What lessons can be drawn for information governance in time-critical digital environments? 4. Assess how the network reflected agile project management in action. Which principles supported adaptability and resilience? Using examples from the case, explain how agility emerged without formal planning tools or leadership hierarchies. 5. Critically examine how credibility replaced hierarchy as a coordination mechanism. How were trust and authority constructed through visible updates, verification, and peer endorsement? Compare this ‘credibility-driven governance’ with formal organisational leadership models. 6. Translate insights from the EndSARS coordination model into concrete design principles. How can participatory data entry, traceable feedback loops, and agile responsiveness be embedded in formal organisational systems without producing noise or duplication? Provide at least one actionable design recommendation. 7. Analyse the tipping point at which visibility undermines coordination effectiveness. Using Galbraith’s Information Processing View (1974), propose ways to structure communication that sustain clarity and accountability under high information pressure. 8. Drawing on the EndSARS experience, design a lightweight coordination protocol for a humanitarian or community-response setting. Balance transparency with control, speed with verification, and decentralisation with trust. Justify your design using one or more frameworks.
Footnotes
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Declaration of conflicting interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.