Category: Digital methodologies series

Big Qual – Why we should be thinking big about qualitative data for research, teaching and policy

When social scientists think about big data, they often think in terms of quantitative number crunching. However, the growing availability of ‘big’ qualitative datasets presents new opportunities for qualitative research. In this post, Lynn Jamieson and Sarah Lewthwaite explore how ‘big qual’ can be deployed as a distinct research methodology to develop new forms of qualitative research and elucidate complex interactions […]

Engaging with sensor-based methods for social sciences research is necessary, overdue and potentially rewarding

Sensors are an important source of big data. Developments at the heart of “smart cities” or the exploding “quantified self” movement are all reliant on sensors. However, attempts by social scientists to engage with sensors from a methodological perspective have been rare. Jörg Müller argues that such engagement is not only necessary and overdue, but also potentially rewarding. It’s important […]

With great power comes great responsibility: crowdsourcing raises methodological and ethical questions for academia

Crowdsourcing offers researchers ready access to large numbers of participants, while enabling the processing of huge, unique datasets. However, the power of crowdsourcing raises several issues, including whether or not what initially emerged as a business practice can be transformed into a sound research method. Isabell Stamm and Lina Eklund argue that the complexities of managing large numbers of people […]

Patient experience feedback: we need to engage with the issues of using Big Data methods to capture the human voice

The NHS regularly asks its patients to complete surveys reporting on the quality of care they have received. These surveys include opportunities for patients to submit feedback in their own words. Carol Rivas describes how computational and digital methods can be used to analyse and report patient feedback in an efficient and timely manner. However, it is important to recognise […]

When data science meets social sciences: the benefits of the data revolution are clear but careful reflection is needed

Contemporary social sciences unquestionably benefit from the growing accessibility and availability of data sources, and the impressive developments in computational tools for data collection and analysis. However, Marta Stelmaszak and Philipp Hukal emphasise the importance of continued careful reflection when using new forms of data and methods. Any analysis of data requires reflection on the agency that went into defining, […]