The dramatic increase over the last two decades or so in computing power, in wired and wireless connectivity, and in the availability of data has affected all aspects of our lives. Our aim in this book is to provide an accessible introduction to how social science researchers are harnessing innovations in digital technologies to transform their research methods. In this chapter we provide an overview of how and why e-Research methods have emerged, including an account of the drivers that have motivated their development and the barriers to their successful adoption.
We are now in an age of almost overwhelming volumes of data about many people’s attitudes, circumstances and behaviour. Such data extends from people’s views to images of them, their locations and movements, and their communications. The data is very diverse; it includes lifelong health and prescription records, genetic biomarker profiles and family histories, satellite images, digital passports and their use, databases from product warranty forms, consumption transactions, online browsing records, email and web communications, social media, and mobile phone use.
This chapter presents case studies of innovative research design, uses of new types of data, data combinations and analysis, and the opportunities and challenges they pose for social science research. The focus is on methods and approaches for analysing and combining data. New data types and analytical approaches open up new opportunities to research previously intractable social problems from different perspectives and in more detail than ever before.
Survey research has traditionally been a process beginning with the formulation of research hypotheses, followed by the construction and testing of a questionnaire, sampling of survey respondents from the eligible population, administration of the survey for data collection, and processing, analysis, and dissemination of the results. This deliberate process has been carried out and refined over the years to provide data to answer many specific research questions.
This chapter focuses on ‘data management’ for social survey research, highlighting its importance and relevance, and describing how e-Research methods can be used to assist in the process of data management in applied social research. e-Research approaches offer facilities for storing and linking data files, and for preserving descriptions of data preparation and analysis routines. Such provisions can help address many of the day-to-day challenges that researchers experience in managing their data.
Quantitative simulation and modelling are perhaps the most obvious examples of the potential for e-Research methods to revolutionize the study of complex socio-economic problems, and their applications are becoming increasingly widespread. This chapter provides an introduction to the state of the art in agent-based modelling techniques, tools and services. The chapter concludes with a discussion of the future for social simulation modelling and e-Research, including remaining obstacles and barriers.
This chapter provides a brief review of current statistical software applications in social science research. It then describes some exciting new developments in interoperability and documentation that have emerged from recent technologically oriented projects. It examines how quantitative social sciences are exploiting the power of new e-Infrastructure and tools.
Text mining has developed dramatically in its power to analyse and extract information from unstructured data. Its applications are motivated by a growing awareness that researchers need more powerful tools in order to cope with rapidly increasing amounts of information and keep abreast of developments within their fields. Using case studies from political communication, this chapter explores how text mining can provide qualitative social researchers with the analytical tools they need for extracting information from unstructured data.
The capacity to capture behaviour through the ‘digital footprint’ that people generate as a by-product of their everyday activities has the potential to transform the practice of empirical social science. The chapter examines how new tools for data collection and analysis make it possible to exploit this data. It focuses on the development of the Digital Replay System (DRS), a software system that enables researchers to combine the data contained in digital records with more traditional and established forms of social science data, such as audio-visual recordings and transcriptions.
The last decade has witnessed a surge in research into social networks using trace data collected from the Web, triggered by the availability of data on social interactions in social network sites such as Facebook and Twitter and information sharing environments such as newsgroups and blogs. This chapter focuses on the study of these online social networks and on the use of the Web as a rich source of born-digital social data.
This chapter presents new ways of visualizing social data, with a particular emphasis on mapping. Web 2.0 mash-ups enable the quick and easy visualization of new and diverse kinds of social data in intuitive ways. The focus is on spatial representations of social and economic data, laced with physical representations of people and places, and drawing on the extensive interest in how people and places interact. Examples featured include both traditional spatial data and new kinds of real-time data from sources such as transit systems and social media.
This chapter reviews some of the challenges that are now emerging for the social sciences as they become more computationally intense. The ability to gather and integrate data in large, centralized data warehouses has led to concerns over data confidentiality, security and possible misuse. The ability to ‘e-enable’ just about any kind of device has led to concerns about privacy, intrusiveness and protection of identity.
This chapter examines the implications of massively increased computational and data resources for social research methods, including the impact on practices and disciplines. The first part of the chapter places the digital in the context of three historical repertoires for apprehending social life: narrative, accounting, and the glance. The chapter then goes on to argue that the digital mimetically enhances all three of these conventional repertoires, at the same time that it emphasizes the exchange, or switch, as having distinctive ontological priority over narratives.