Examples of using Big data sources in English and their translations into Vietnamese
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I think the idea of repurposing is fundamental to learning from big data sources, and so, before talking more specifically about the properties of big data sources(section 2.3)
More generally, rather than trying to argue that big data sources are better
fundamental limitations of big data sources, and how they can be overcome with surveys, are illustrated by Moira Burke and Robert Kraut's(2014)
Further, although the earlier eras were characterized by their approaches to sampling and interviewing, I expect that the third era of survey research will also be characterized by the linkage of surveys with big data sources(Table 3.1).
examine the extent to which they are applicable to big data sources, and Puts, Daas,
examine to which extent they are applicable to big data sources, and Puts, Daas,
I describe big data sources in more detail and clarify a fundamental difference between them and the data that have typically been used for social research in the past. Then, in section 2.3, I describe ten common characteristics of big data sources.
new approaches to measurement(section 3.5), and new strategies for combining surveys with big data sources(section 3.6).
to ask different kinds of questions, and to magnify the value of survey data with big data sources.
but cleaning big data sources is more difficult for two reasons: 1 they were
number of steps to check the results of these two steps- even though some of them are proprietary- and these checks might be helpful for other researchers wishing to link survey data to black-box big data sources.
Hersh go through a number of steps to check the results of these two steps-even though some of them are proprietary-and these checks might be helpful for other researchers wishing to link survey data to black-box big data sources.
of field experiments when(1) heterogeneity in effects is important and(2) the important variables needed for matching have been measured. Table 2.4 provides some other examples of how matching can be used with big data sources.
researchers using this approach need to be especially concerned about possible biases caused by who is included-and who is not included-in their big data source.
Big data sources are both found and designed;
Big data sources tend to have ten characteristics;
Surveys linked to big data sources(section 3.6).
Big data sources can be loaded with junk and spam.
Table 2.3: Examples of natural experiments using big data sources.
Table 2.3: Examples of natural experiments using big data sources.