Abinaya Chandrasekar ¹ Sigrún E. Clark ¹ Sam Martin ^1,2 Samantha Vanderslott ² Elaine C. Flores ³ David Aceituno ⁴ Cecilia Vindrola-Padros ¹ Norha Vera San Juan ^1*

• ¹ Department of Targeted Intervention, Division of Surgery and Interventional Science, Faculty of Medical Sciences, University College London, London, England, United Kingdom
• ² Oxford Vaccine Group, Oxford, England, United Kingdom
• ³ Centre on Climate Change & Planetary Health, London School of Hygiene and Tropical Medicine, University of London, London, England, United Kingdom
• ⁴ School of Medicine, Faculty of Health Sciences, Pontificia Universidad Catolica Madre y Maestra, Santiago, Santiago, Dominican Republic

Qualitative data provides deep insights into an individual’s behaviours and beliefs, and the contextual factors that may shape these. Big qualitative data analysis is an emerging field that aims to identify trends and patterns in large qualitative datasets. The purpose of this review was to identify the methods used to analyse large bodies of qualitative data, their cited strengths and limitations and comparisons between manual and digital analysis approaches. A multi-faceted approach has been taken to develop the review relying on academic, grey and media-based literature, using approaches such as iterative analysis, frequency analysis, text network analysis and team discussion. The review identified 520 articles that detailed analysis approaches of big qualitative data. From these publications a diverse range of methods and software used for analysis were identified, with thematic analysis and basic software being most common. An important finding was identifying an increase in the use of larger non-traditional qualitative data sources (social media data, images and videos) and methods and (semantic network analysis, topic modelling, and the breadth and depth method) in more recent publications.Studies were most commonly conducted in high-income countries, and the most common data sources were open-ended survey responses, interview transcripts, and first-person narratives. We identified an emerging trend to expand the sources of qualitative data (e.g. using social media data, images, or videos), and develop new methods and software for analysis. As the qualitative analysis field may continue to change, it will be necessary to conduct further research to the compare the utility of different big qualitative analysis methods and to develop standardized guidelines to raise awareness and support researchers in the use of more novel approaches for big qualitative analysis.