This book attempts to bring together social scientists and data scientists to create something more beneficial and interesting. In the analog world, collecting data about behaviour was expensive and hence rarely carried out. However, at present, in the digital world, the behaviour of billions of people is recorded, stored and analysable. While there are excessive digital traces now, using them for social research can be capricious. Many researchers tend to place emphasis on online data generated and obtained by companies such as search engine logs and social media posts. However, two other important sources of big data are being left out in the process. They include corporate big data sources from digital devices in the physical landscape and government administrative records.
The ten common characteristics of big data include: big; always on; nonreactive; incomplete; inaccessible; non-representative; drifting; algorithmically confounded; dirty; and sensitive. Hence, in comparison to traditional social research methods, many sources of big data can be used to study behaviour that has not be amenable to accurate measurement previously because participants are now nonreactive. While the digital era has led to wider options for collecting and analysing social data, but at the same time it has also bring about new ethical issues.
Nonetheless, the future of social research has been considered to be a combination of social science and data science, where they will be more participant-centred data collection. In addition, ethics will shift from being a secondary to primary concern and a topic of research in its own right.
Participate in the upcoming QS Subject Focus Summit – “Humanities and Social Sciences Research” which will be held from 29-31 August 2018 in Venice, Italy.