Human computation enables you to have a thousand research assistants.
Human computation projects combine the work of many non-experts to solve easy-task-big-scale problems that are not easily solved by computers. They use the split-apply-combine strategy to break a big problem into lots of simple micro-tasks that can be solved by people without specialized skills. Second generation human computation systems also use machine learning in order to amplify the human effort.
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. These classifications are not an end; they are the raw materials for research. For example, the crowd-coding of political manifestos could be used to test theories about the dynamics of attention toward migration.
In order to further build your intuition, Table 5.1 provides additional examples of how human computation has been used in social research. This table shows that, unlike Galaxy Zoo, many other human computation projects use micro-task labor markets (e.g., Amazon Mechanical Turk). I’ll return to this issue of participant motivation when I provide advice about creating your own mass collaboration project.
| Summary | Data | Participants | Citation |
|---|---|---|---|
| coding party manifestos | text | micro-task labor market | Benoit et al. (2015) |
| extract event information from news articles on the Occupy Protests in 200 US cities | text | micro-task labor market | Adams (2014) |
| classification of newspaper articles | text | micro-task labor market | Budak, Goel, and Rao (2016) |
| extracting event information from diaries of soldiers in World War 1 | text | volunteers | Grayson (2016) |
| detect changes in maps | images | micro-task labor market | Soeller et al. (2016) |
Finally, the examples in this section show that human computation can have a democratizing impact on science. Recall, that Schawinski and Lintott were graduate students when they started Galaxy Zoo. Prior to the digital age, a project to classify a million galaxy classification would have required so much time and money that it would have only been practical for well-funded and patient professors. That’s no longer true. Human computation projects combine the work of many non-experts to solve easy-task-big-scale problems. Next, I’ll show you that mass collaboration can also be applied to problems that require expertise, expertise that even the researcher herself might not have.
