Examples of using Digital trace in English and their translations into Vietnamese
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The same is not true for your digital traces.
Another way that researchers can use digital traces and administrative data is a sampling frame for people with specific characteristics.
Big Data means that everything we do, both on and offline, leaves digital traces.
And, unlike some of the other problems with digital traces, algorithmic confounding is largely invisible.
Big Data also means that everything we do, whether on the net or outside,leaves digital traces.
Subsequently many, many other projects have tried to use digital trace data for disease surveillance detection, see Althouse et al.
The emergence of Big Data has meant that everything we do, online or off-,leaves digital traces.
In particular, I will focus on digital trace data and administrative data where the researcher had no role in the creation of the data.
Table 2.5: Partial list of studies use some digital trace to predict some event.
Because these data are a by-product of people's every day actions,they are often called digital traces.
This method of surveillance, though effective, is risky, as it leaves a digital trace that counter-surveillance experts from foreign governments could detect.
The emergence of Big Data has meant that everything we do, online or off-,leaves digital traces.
The dangers of dirty digital trace data are illustrated by Back and colleagues'(2010) study of the emotional response to the attacks of September 11, 2001.
First, for the people in both data sources,build a machine learning model that uses digital trace data to predict survey answers.
In enriched asking, on the other hand, the digital trace actually has a core measure of interest and the survey data builds the necessary context around it.
There is just too much to be gained by linkingsurvey data to other data sources, such as the digital trace data discussed in Chapter 2.
In addition to using digital trace data to predict health outcomes, there has also been a huge amount of work using Twitter data to predict election outcomes;
Whether you are going for a run, watching TV or even just sitting in traffic,virtually every activity creates a digital trace- more raw material for the data distilleries.
The three sources of drift mean that any pattern in digital trace data could be caused by an important change in the world, or it could be caused by some form of drift.
Whether you are going to run, watching TV or even just sitting in traffic,virtually every activity creates a digital trace- more raw materials for data distilleries.
A different approach to dealing with the incompleteness of digital trace data is to enrich it directly with survey data, a process that I will call enriched asking.
Although these details are specific to this study, issues similar to these will arise forother researchers wishing to link to black-box digital trace data sources.
Thus, if there is some question that you want to ask to lots of people,look for digital trace data from those people that might be used to predict their answer.
For researchers not familiar with the idea of construct validity, Table 2.2 provides some examples of studies thathave operationalized theoretical constructs using digital trace data.
In conclusion,Blumenstock's amplified asking approach combined survey data with digital trace data to produce estimates comparable with gold-standard survey estimates.
The dangers of dirty digital trace data are illustrated by Back and colleagues'(2010) study of the emotional response to the attacks of September 11, 2001, which I briefly mentioned earlier in the chapter.
Whether you are going for a run, watching TV or even just sitting in traffic,virtually every activity creates a digital trace- more raw material for the data distilleries.
The two ingredients are 1 a digital trace dataset that is wide but thin(that is, it has many people but not the information that you need about each persons) and 2 a survey that is narrow but thick(that is, it has only a few people, but it has the information that you need about those people).
Using search data to predicting influenza prevalence and using Twitter data to predictelections are both examples of using some kind of digital trace to predict some kind of event in the world.
