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How to… use crowdsourcing as a research tool

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Article Sections

  1. Introduction
  2. What is crowdsourcing, why is it used and how does it work?
  3. Academic uses of crowdsourcing
  4. How to succeed at crowdsourcing
  5. Conclusion
  6. References

What is crowdsourcing, why is it used and how does it work?

Crowdsourcing involves three elements:

  1. A problem or task is assigned to a wide, and random, audience [the crowd], rather than a selection of experts.

  2. The crowd then generates shared content, on a voluntary basis (although there may be some small payment), which may be data to resolve a particular problem (for example, where people are asked questions about images), or a collection of memorabilia associated with a particular community (for example, , which documents the effects of the Olympics on the lives of East Londoners).

  3. The above activities are facilitated by online technology.


Projects meeting the first two criteria are not new: for example, the Oxford English Dictionary used volunteers to provide citations of word use.

However, the term “crowdsourcing” was first used by Jeff Howe in a 2006 Time magazine article, to describe the phenomenon of online content created by amateurs.

Howe recently wrote a book, Why the Power of the Crowd Is Driving the Future of Business (Howe, 2008), which looks at online examples of crowdsourcing from the business and scientific worlds: you can read a review .

Why use crowdsourcing?

Why use the crowd rather than experts, and why should people volunteer their time to provide content to a website when it is so much easier just to browse what is there?

A cynical response to the former question is that it comes down to funding.  Goodchild (2007), in discussing the phenomenon of volunteered geography, claims that citizen input to mapping helps fill a hole created by the decline in government funded mapping (p.217).

The challenges of funding, as well as the ease with which anyone can upload content to the Internet, have, according to the UK’s Joint Information Systems Committee (JISC), changed the way in which online collections are created and used (JISC, 2010).

There may, however, be genuine statistical reasons why the crowd, by its nature diverse, performs better than experts. Take prediction, for example: when the disparate guesses of a large number of people are averaged out, the results are often better, and more accurate, than that of an individual expert.

It’s a phenomenon which has been used by researchers at George Mason University to study ways in which crowdsourcing can help in intelligence gathering.

And in some cases, the crowd may have better knowledge than the expert. According to Goodchild (2007), locals may be able to provide early warning of natural disasters because they are familiar with the area, whilst satellites only pass infrequently.

As to why people volunteer their time, one explanation is the desire to contribute to the common good, and to gain recognition from others, as is the case with the academic community (JISC, 2010, p. 7). 

Upshall (2011) suggests other reasons: interest in the subject, ease of contribution, and some form of reward, which may or may not be financial.