Public Administration researchers are facing the opportunities and challenges to analyze large-scale datasets that are either passively created through online interactions between devices, websites, or social media users, and can be actively harvested by resources through open application programming interfaces (APIs) and derive meaningful implications for theory and practice. Big data is currently used as an umbrella term to describe the amount of data, as well as computational practices to harvest large-scale datasets from multiple different sources, analyze them in real-time, draw immediate conclusions from them, and act on the resulting outcomes. Big data focuses mostly on new forms of (social) data generated by Internet users, such as networks created through follower relationships on social networking sites, links between websites, or mobile phone connections and use of mobile apps in combination that can be combined with the users’ socio-demographic data. The study of these big data sets – huge amounts of that usually go beyond the computing power and analytic scope of social scientists – has emerged as a field that combines datasets, usually freely available for download from the web, with existing social science methods and theoretical perspectives, the application of computer science methods, and the revision of existing social science analytical methods (Lazer et al., 2009). For public administration researchers the multi-modal nature and access to freely available data provides new opportunities: big data sets are continuously and oftentimes automatically created and accessible through the application interfaces of the (social networking) sites that allow its users to participate in the creation of content and interactions. It has even become relatively easy for non-computer scientists to download these datasets and harvest the content and frequency of social media interactions (Hansen, Shneiderman, & Smith, 2010). For public administration researchers there is therefore an opportunity to create highly detailed insights from many different data points about individual subjects, instead only on administratively collected data, such as anonymized census data. The nature of the data – its volume, velocity, but also the value that can be derived from it in almost near real-time can be used to draw insights about emerging patterns of social behavior that has not been available to public manager before. Similar real-time insights can be created across many different policy and implementation areas in the public sector and used to increase early awareness for public management problems and the insights can be included as additional data points to improve decision making capacity among public managers.
In this paper, we first review the existing literature on Big Data research in the neighboring disciplines, such as Public and Social Policy, Business Management, Political Science, Economics, as well as newer disciplines, such as Computational Social Sciences, or Policy Informatics. We then derive opportunities for Big Data applications in the public sector and specifically for the creation of early signaling, increasing awareness, and real-time insight purposes. The conclusions will focus on implications for practitioners as well as public management researchers.