Innovations in Digital Research Methods. Группа авторов

Innovations in Digital Research Methods - Группа авторов


Скачать книгу
Census will be the last full census in the UK and there will be a shift in the future to smaller-scale data gathering and use of administrative records.41

      The LFS is a quarterly survey of over 60,000 households. The LFS is now linked with the UK Annual Population Survey and includes increased coverage of urban areas down to local authority district level. The data includes a longitudinal component, with respondents being interviewed five times at three-monthly intervals. Questions cover such variables as people’s key demographics and occupation, training, health, earnings and benefit claims. Some of the measures are internationally comparable. Access to the data from such surveys as the LFS is often free (although usage is not completely unrestricted).

      For many survey datasets, access to particular variables, geographic levels and detailed information is restricted because of concerns about confidentiality and statistical disclosure risks.42 For example, only samples of UK Census data and certain variable codings are released at particular geographic levels. This can inhibit analysis at lower geographies. For some government surveys and datasets, special licence use versions are available which contain more detailed variable codings and geographic information.

      Other sources of data on people’s economic circumstances include income data available from commercial data providers. The data is updated from different sources, including surveys and other data gathering tools such as product warranty forms. Such data provides income estimates at the individual level, though these are often imputed. Many of the variables have bounded values, for example, age and income are in bands. Other variables cover people’s spending, savings and debts.

      Consequential data, such as administrative data, including information on earnings, tax payments and benefits claims, are held by government departments and, if not released directly, can be available for social science research purposes under special agreements. Some commercial information is also available in the public domain. For example, organizations such as estate agents necessarily release data on properties on their books as part of their core business. If made available for research purposes, data from the Citizens Advice Bureau (CAB), and agency and bank consultations concerning debt advice, which includes anonymized client details, type of problem, advice given and outcomes, could also be examined alongside publicly available data from land records and on share ownership.

      Open data resources such as OpenStreetMap43 can be used to map areas of deprivation and can be combined with official data such as the ONS Neighbourhood Statistics.44 For research into the impact of the economic recession on people’s lives, consequential data from Internet searches for credit advice and locations of cash conversion shops could be of value. Self-published data such as online discussion groups and forums could be used for examining people’s attitudes towards the recession and their coping behaviour. For example, the online network and web resource Mumsnet, which is a self-selected online network of parents, has a large number of postings from its members on the recent economic recession. In addition, the organization itself has conducted a survey of its members on the issue of household spending. Example (anonymised) Mumsnet discussion group comments include:

      I have to cook on a very tight budget so when I go shopping I go straight to the reduced selection and always stock up with as much reduced food as possible and either cook it that night and freeze it down, or freeze it straight away. That way my family can eat very healthy for a fraction of the price. (‘TAM’, 2011)45

      Here, the social science researcher might code for key information, as they would do in a conventional qualitative textual analysis. This might include coding for: gender, type of food planning, attitude to cooking, healthy eating and family, language use, and comment length. Links to other posts might also yield even richer data. The researcher could also take a direct follow-up approach including posting messages to the online group, collecting information using methods such as purposive surveys, follow-up interviews and online discussions (effectively purposive online focus groups). The key challenge here in terms of social science research lies in the purposive nature of the samples and the limits to what can be claimed about any patterns identified in such self-published data.

      Closely linked to data on people’s economic circumstances is evidence on people’s consumption behaviour and we now consider this.

      2.3.2 Data on Consumer Behaviour

      In the UK, a key survey of consumer behaviour and household spending is the Family Resources Survey (FRS),46 which is a continuous survey with an annual target sample size of 24,000 private households. The survey began in 1992. Households interviewed in the survey are asked a wide range of questions about their key demographics and their circumstances (including receipt of welfare benefits, housing costs, assets and savings). An end-user licence version of the data with reduced detail is available via download from the UK Data Service. A special licence version of the FRS is available to approved researchers via the Secure Data Service as described above. The special licence version includes additional variables and increased detail on some variables, particularly geographic location.47 Access to such data is free or available for a minimal administration fee.

      Real time consumption data (a type of consequential data) is also now collated by online companies and supermarkets via loyalty cards. Such data are held on restricted access databases; however, samples have been made available for social science researchers.48 The data are of considerable commercial value to the companies and organizations that collect and warehouse them. Alongside individual records of behaviour, data mining techniques can be used to identify associations and patterns in the data. For example, the company Dunnhumby works closely with supermarkets and other retailers examining purchasing patterns in order to target marketing and product range, and optimize the personalization of consumer experience.49 Consumer profiling organizations such as CACI provide data products that contain hundreds of individual-level variables including income, spending, media consumption and types of leisure activities.50 As outlined above, these data products link multiple sources including: surveys, product warranty forms, public records, administrative records such as the Electoral Register, house sale information and consumption records.

      Online search engines such as Google and retailers such Amazon collate search patterns and profile customers by page visits and purchases. Samples of this data (for example, Google Trends and Google Analytics) are made available either freely or for purchase. In terms of administrative records, government departments hold consequential data on benefits claims and payments at the individual level. This could, in principle, be combined with survey data to research patterns in consumer behaviour. Such databases can be so large that the importance of making inferences from a sample to a population is of less concern for certain types of research.

      2.3.3 Data on Health and Well-being

      The Health Survey of England (HSE)51 and the English Longitudinal Study of Ageing (ELSA)52 are two key surveys for examining health outcomes. The HSE is a representative survey of around 15,000 adults and children in England. It combines data on attitudes towards health, eating and exercise with physiological data. Core topics include: general health, smoking, drinking, fruit and vegetable consumption, height, weight, blood and saliva samples. Special topics include: cardiovascular disease, physical activity, accidents, lung function measurement,


Скачать книгу