Crowdsourcing for dummies – a beginners guide

In these first few posts on Crowd Around, I intend to give some background on why crowdsourcing and social media are topics worthy of your attention.

It seemed a good starting point then, to define what the term crowdsourcing encompasses. In doing this I pulled down a definition from Wikipedia. I was immediately struck by the irony, as Wikipedia is probably one of the best known examples that demonstrate the benefits and transformational power of crowdsourcing. Here it is:

Crowdsourcing is a distributed problem-solving and production model. Problems are broadcast to group of solvers in the form of an open call for solutions. Users — also known as the crowd — typically form into online communities, and the crowd submits solutions. The crowd can also sort through solutions to find the best ones. These best solutions are then owned by the entity that broadcast the problem in the first place — the crowdsourcer — and the winning individuals in the crowd are sometimes rewarded. In some cases, this labour is well compensated, either monetarily, with prizes, or with recognition. In other cases, the only rewards may be kudos or intellectual satisfaction. Crowdsourcing may produce solutions from amateurs or volunteers working in their spare time, or from experts or small businesses which were unknown to the initiating organization

I would expand this further to describe the role of the crowdsourcer: a facilitator and architect that designs a structure that enables and provides incentives for user participation.

I have included this definition here verbatim. It’s a succinct description that has been drafted, reviewed, enhanced and maintained by the Wikipedia editorial community. Crowdsourcing is a fairly new concept with few experts in the world – the fact Wikipedia can keep up to date with rapidly evolving ideas in a field like crowdsourcing is an incredible achievement.

So how does Wikipedia use crowdsourcing? Jimmy Wales, founder of Wikipedia, has designed an open yet controlled hierarchical collaborative system that allows anyone to contribute to a topic. Several mechanisms are in place to ensure quality, with editors able to monitor pages manually and programmatically to ensure the content is in line with current expert opinion.

The incentives at work here are similar to those found in the scientific community: a desire to publish true facts about the world, to share knowledge and fundamentally: to receive recognition or credit among peers in the contributor’s community. While Wikipedia doesn’t credit authorship, authors often claim to know each other and frequently discuss and contribute to topics they are well known for within their community of expertise. For every professor and scholar denouncing the inaccuracy of a particular topic on Wikipedia, there are ten actively editing the wiki to improve the quality.

It clearly works. A crowd of 85,000 contributors, 14,000,000 articles and 65,000,000 monthly visitors are evidence of that. The currency, accessibility and breadth of content on Wikipedia has left predecessors Britannica and Microsoft Encarta in the dust. The architecture of openness, collaboration and contribution incentives is a perfectly executed example of using a crowdsourcing model to create an immeasurably valuable resource.

So what lessons can we draw from the success of Wikipedia? If we consider what characteristics make crowdsourcing such an effective model for encyclopaedic web publishing, can we identify other industries ripe for introducing a crowdsourcing solution?