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How to… use crowdsourcing as a research tool

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Academic uses of crowdsourcing

Apart from citizen science projects such as Galaxy Zoo, the main applications of crowdsourcing to academe lie in the areas of geospatial data, of digital content collections round a particular theme, and crowdsourcing of non-complex but non-automatic tasks, often connected with heritage documents. Another interesting use is in the area of intelligence.

Geospatial data

According to Andy Hudson-Smith of the Centre for Advanced Spatial Analysis (CASA) at University College London (Hudson-Smith, 2011), crowdsourcing methods have a particular application to geography through Volunteered Geographic Information.

CASA uses a number of different techniques to represent space-time data in pursuit of its research on city systems. The data is explored through a wide range of methods including social physics, statistical models, augmented reality – and crowdsourcing.

Working with colleagues at the School of Geography at the University of Leeds, CASA has been developing large-scale toolkits to facilitate the collection of data by crowdsourcing.

One such tool is , which enables any user to quickly set up a survey and collect a large amount of data which can be shown on a map.

Surveys can be on any topic, from complex world issues such as climate change to the more personal (such as how happy are you) and pragmatic, such as how fast is your broadband speed or how do you get to work.

Despite, or because of, its ease of use, SurveyMapper has been used extensively by the academic community, as well as the BBC.

Image: Example of a survey from SurveyMapper
Example of a survey from SurveyMapper

CASA is developing a number of other toolkits suitable for large data capture:

  • , a tool which enables novice users to create complex maps. Publicly available or crowd-sourced data on any topic can be overlaid on freely available mapping services such as Google Maps or Open Street Map.

  • : geospaTial datA anaLysIS & SiMulAtioN. This project will develop methods for geospatial data analysis, looking specifically at interactions which reflect potential flows in and between locations.

  • The "", which can mine and analyse data from Twitter, linking it to 16 global cities.

Quercia et al. (2012) provide an example of Twitter being used for social research: they analysed tweets according to "topic models" and were able to demonstrate a correlation between topic and community deprivation.

Community collections

These involve members of communities uploading content – photos, letters, descriptive accounts, etc. – to a particular online collection point on a particular theme.  The collection may be managed by a library, museum, or university, but the items in the collection are supplied by volunteers.

Two important such collections, both funded by the UK’s JISC, are:

  • , which is a "living archive" documenting the experience of Londoners around and in the run-up to the 2012 Olympics and Paralympics. Residents, schools and taxi drivers were interviewed, and there was a particular focus on the Olympic bid pledges of community regeneration and greater health and well-being.

  • : the public were invited to send in digital memorabilia, or family stories handed down through generations. The result was a unique collection of primary material which tells the story of the First World War from the point of view of the ordinary soldier.

Another community-based collection, this time of research, not funded by JISC and international, is database of research literature. The Mendeley software is scaled to handle 120 million uploaded documents and hold seven terabytes of data.

Projects which crowdsource a task

There are a number of projects which use crowdsourcing to outsource a particular task or set of tasks.

Most such projects are cultural or heritage-based. Two examples are:

  • The project, where volunteers transcribe, from scratch, adding  TEI XML tags, the rough notebooks of the famous philosopher, which are heavily annotated and corrected.
  • , the collaborative translation of which is being managed by the University of Michigan.

The complexity of the above projects places great demands on volunteers: in the case of the Encyclopédie, the requirement to understand 18th-century French has limited the take-up.


A rather unusual application of crowdsourcing is being deployed by the US intelligence community.  Several groups of researchers are looking at ways of harnessing the power of crowds to predict future events.

The project is , Decomposition-based Elicitation and Aggregation, and is lead by a team based at George Mason University.

Researchers crowdsourced through blog postings and Twitter, asking participants to comment and predict on particular world events, for example the stability of Kim Jong Il’s regime in North Korea.

The predictions are then broken down into variables, the questions themselves into smaller parts so that the respondent can answer that part that best approximates to his or her knowledge.

The idea is to have a “heads up” on momentous world events, such as, say, the Arab Spring.