Rapid Insight, Real Impact: The Role of Thematic Analysis in Crisis Research
In times of crisis, the need for insight is immediate, and the stakes are high. Whether it’s a global pandemic, a natural disaster, or a sudden political upheaval, researchers are often called on to understand fast-changing situations and provide timely, actionable findings. But insight isn’t just numbers. In moments like these, qualitative research plays a vital role in helping us understand what people are experiencing, how systems are holding up, and what matters most.
The challenge here, is time.
Traditional qualitative methods often require weeks or months of manual coding, sense-making, and synthesis. But in a crisis, we don’t always have that luxury. That’s where rapid, structured thematic analysis makes all the difference.
This post explores how Leximancer has helped researchers and organisations respond effectively in moments of uncertainty. From COVID-19 to climate-driven disasters, we look at how crisis research is evolving, and what it takes to deliver depth at speed.
Why Speed and Structure Go Hand in Hand
To be clear, moving quickly doesn't mean cutting corners.
When thematic analysis is done well, it offers something quantitative data often can’t. That being context, emotion, and a window into lived experience.
During a crisis, those insights are priceless. They can inform urgent policy decisions, shape public messaging, and guide resource allocation. But they need to come quickly enough to matter. That’s why more researchers are turning to automated tools like Leximancer to support fast, reproducible qualitative work.
Case Example: COVID-19 Emergency Response
When COVID-19 hit, healthcare workers were stretched beyond capacity. In Queensland, Australia, a large public hospital network launched a series of internal webcasts to gather frontline feedback in real time. Nurses, doctors, and hospital staff spoke candidly about safety fears, leadership gaps, PPE shortages, and emotional exhaustion.
The transcripts from these sessions became an invaluable source of data, but also a logistical challenge. Researchers from the University of Southern Queensland were tasked with making sense of the content quickly enough to inform leadership decisions.
They applied both manual coding and Leximancer’s automated analysis to 20 transcripts. Leximancer surfaced the same core concerns …like safety, teamwork, workload, and support… but in a fraction of the time. More beneficially, it visually mapped how these ideas were connected, revealing subtle tensions (e.g. between “leadership” and “clarity”) that manual coding hadn’t discovered.
“The Leximancer analysis was completed within hours and provided a similar output to the manual thematic analysis which took weeks to complete.”
— Wiedemann et al., 2021
These insights were used not just to document experiences but with an aim to change conditions. Hospital administrators implemented immediate changes to communication protocols and staffing models, citing the real-time thematic feedback. The research team described Leximancer as instrumental in helping transform emotional frontline narratives into structured, strategic recommendations.
Case Example: Discourse Analysis Reframing Tourism
The COVID-19 pandemic also shook the global tourism industry to its core. Cancellations, lockdowns, and international border closures halted an entire economic ecosystem overnight. But the disruption was more than financial by forcing the industry to confront its values, fragility, and identity.
A group of researchers used Leximancer to analyse international discourse around tourism during the crisis. Their aim was to understand how the language itself was changing.
They found that pre-pandemic narratives centred on growth, recovery, and market strategies. But during the crisis, these themes gave way to deeper concerns: resilience, community, dignity, and loss.
“There is an urgent need for tourism to be reimagined. Our analysis highlights a discursive shift - from growth and recovery to resilience, dignity, and wellbeing.”
— Cheer et al., 2021
Leximancer made it possible to process large-scale qualitative data quickly, and more importantly, to see the semantic shifts happening in real time. These insights helped position the researchers at the centre of global discussions about the future of sustainable and equitable tourism, and influenced how recovery funds were allocated and how future campaigns were framed.
Case Example: Mapping Community Priorities Post-Bushfire
The 2019–2020 Australian bushfires were one of the country’s most devastating climate disasters. As communities mourned the loss of homes, ecosystems, and lives, the online space became a key outlet for public grief, anger, and debate.
Researchers Wang and Khoo-Lattimore turned to Twitter to understand this unfolding narrative. Analysing over 100,000 tweets, they used Leximancer to track how themes like leadership, wildlife, environment, and climate change surfaced and shifted in the days and weeks following the fires.
“Leximancer was effective in identifying emergent and evolving issues... providing real-time feedback for recovery strategies.”
— Wang & Khoo-Lattimore, 2021
The visual maps generated by Leximancer made it possible to trace semantic associations, such as the growing link between “climate change” and “leadership failure”, that signalled rising public frustration with political inaction. These insights weren’t just descriptive but strategic. Policymakers used the analysis to prioritise relief messaging, support mental health initiatives, and adapt tourism campaigns in fire-affected regions.
Doing Fast Qualitative Research—Well
Crisis research doesn’t have to mean rushing. But it does mean choosing methods that can deliver results in the time you need them. Here are a few guiding principles:
Simplify data prep: Clean, structured text inputs speed up the process.
Let concepts emerge naturally: Avoid rigid pre-coding. Let the software surface what’s really in the data.
Visualise to communicate quickly: Concept maps can be more impactful than pages of prose.
Validate with human insight: Automated tools don’t replace researchers—they free them to do the deeper thinking.
In a crisis, every moment counts. But fast research doesn’t have to mean shallow research.
Thematic analysis done right can give organisations a clear window into what’s working, what’s failing, and how people are really feeling. It adds nuance to numbers, emotion to statistics, and context to action.
And sometimes, that’s exactly what’s needed to turn a moment of chaos into meaningful, human-centred change.
