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Velká data jako alternativa výběrových šetření v kvantitativním sociálněvědním výzkumu

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Chylíková J.
Naše společnost (Our Society)
|
2018
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vol. 16
|
issue 1
57-79
EN
The goal of this article is to inform social scientists, especially those of a quantitative orientation, about the basic characteristics of Big Data and to present the opportunities and limitations of using such data in social research. The paper informs about three basic types of Big Data as they are distinguished in contemporary methodological literature, namely administrative data, transaction data and social network data, and exemplifies how they can be utilized by quantitative social research. According to many, questionnaire-based sample survey as the dominant method of quantitative social research has found itself in a crisis, especially as response rates have decreased in most developed countries and public confidence in opinion polling has declined. The author presents the characteristics and specifics of Big Data compared to survey research - a method whose primary distinguishing characteristic is the capacity to quantify individual behaviour, social action and attitudes at the level of populations. In this context, the article draws attention to the differences between Big Data and survey data typically presented in scholarly literature, namely that datasets are not representative of known populations, the values of observed variables are systematically biased, there is a limited number of variables in Big Data sets, there is uncertainty about the meaning of observed values, and social environment has direct influence on the behaviours captured by Big Data. Attention is also paid to such characteristics of Big Data that pose an obstacle to smooth integration of this type of data in the social scientific mainstream. First, the collection, processing and analysis of Big Data is extremely demanding in terms of programming skills, something social scientists typically do not have. Second, the availability of Big Data is limited as they are normally possessed by private corporations, some of which (Facebook, Google) have undoubtedly come to form data oligopolies - and their management is mostly unwilling to share their data with traditional academics. Based on the above-mentioned specifics, differences and limitations, it is argued that Big Data currently do not have the potential of becoming a full-fledged source of social science data and replacing sample surveys as the dominant research method. Finally, the article draws attention to the specifics of different types of Big Data as they are primarily generated for purposes other than social research and result from specific situations framed by existing social relations - and it is from this perspective that Big Data should be viewed by social researchers.
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Odhad reliability vybraných položek z českých šetření EU SILC kvazisimplexovým modelem

100%
Chylíková J.
Sociologický časopis. Czech Sociological Review
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2016
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vol. 52
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issue 1
79-106
EN
The article presents estimates of the reliability of measurement in the Czech surveys carried out in the EU-SILC international longitudinal research project. The reliability estimates were obtained using the Quasi Simplex Model (QSM), which has never before been used in Czech research. An analysis was carried out on all the items in the EU-SILC questionnaire that fulfilled the criteria for the QSM analysis: PH010, the item that asks respondents about their subjective health, HS120, the item that asks about the household’s financial situation, and HS130, which asks what the minimum sufficient income of a household is. The analysis drew on all available data from Czech EU-SILC surveys, that is, data from five rotating panel surveys carried out between 2005 and 2012. The QSM analysis showed that for the selected items EU-SILC data are highly reliable; the estimated reliability of each item was around 0.8, for HS130 it was even above 0.9. The steadiness of the results was confirmed by the high consistency of the reliability estimates across all the panels. A small difference was observed between the reliability of data collected using the PAPI mode and data collected using CAPI. Given the attributes of the QSM model, however, it was impossible to test statistically whether the reliability of PAPI and CAPI data differ significantly.
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