Examples of using Human computation projects in English and their translations into Urdu
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Table 5.1: Examples of human computation projects in social research.
Now I can also highlight two important differences between open call projects and human computation projects.
This comparison shows that, as with Galaxy Zoo, human computation projects can produce high-quality results.
It is these easy-for-people yet hard-for-computers microtasks that we can turn over to human computation projects.
This comparison shows that, as with Galaxy Zoo, human computation projects can produce high quality results.
Human computation projects are ideally suited for easy-task-big-scale problems, such as labeling a million images.
It is these easy-for-people yet hard-for-computers micro-tasks that we can turn over to human computation projects.
Human computation projects take a big problem; break it into simple pieces; send them to many workers; and then aggregate the results.
This table shows that, unlike Galaxy Zoo, many other human computation projects use micro-task labor markets(e.g., Amazon Mechanical Turk).
Two clever human computation projects that I did not have space to discuss are the ESP Game(Ahn and Dabbish 2004) and reCAPTCHA(Ahn et al. 2008).
The term“split-apply-combine” was used by Wickham(2011) to describe a strategy for statistical computing,but it perfectly captures the process of many human computation projects.
Human computation projects combine the work of many non-experts to solve easy-task-big-scale problems that are not easily solved by computers.
In social research, human computation projects are most likely to be used in situations where researchers want to classify, code, or label images, video, or texts.
Human computation projects take a big problem, break it into simple pieces, send them to many workers, and then aggregate the results.
Galaxy Zoo, and other human computation projects, typically use a split-apply-combine strategy(Wickham 2011), and once you understand this strategy you will be able to use it to solve lots of problems.
In human computation projects, researchers combine the efforts of many people working on simple micro-tasks in order to solve problems that are impossibly big for one person.
Galaxy Zoo, and other human computation projects, typically use a split-apply-combine strategy(Wickham 2011), and once you understand this strategy you will be able to use it to solve lots of problems.
For example, in the human computation project described below, the same recipe will be followed, but the apply and combine steps will be quite different.
Coding political manifestos, something typically done by experts,can be performed by a human computation project resulting in greater reproducibility and flexibility.
Second, by some definitions of human computation(e.g., Von Ahn(2005)), FoldIt should be considered a human computation project.
By this definition FoldIt- which I describedin the section on open calls- could be considered a human computation project.
Kenneth Benoit and colleagues(2016) decided to take the manifesto coding task that had previously been performed by experts andturn it into a human computation project.
If this approach does not scale well,the researcher can move to a human computation project with many participants.
A classic example of a human computation project is Galaxy Zoo, where a hundred thousand volunteers helped astronomers classify a million galaxies.
For example, in the human computation project described below, the same recipe will be followed, but the apply and combine steps will be quite different.
I call this a computer-assisted human computation project because, rather than having humans solve a problem, it has humans build a dataset that can be used to train a computer to solve the problem.
First, one way that I distinguish between human computation and open call projects is whether the output is an average of all the solutions(human computation) or the best solution(open call).
In human computation and distributed data collection projects, on the other hand, the best form of quality control comes through redundancy, not a high bar for participation.
In addition to creating human computation and open call projects, researchers can also create distributed data collection projects.
To make this a bit more concrete, let's return to Galaxy Zoo, the human computation astronomy project discussed earlier in this chapter.