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As it is typical for an emerging area, Crowdsourcing also has been classified in many ways. It has also been referred to as by different names such as peer production, user-powered systems, user-generated content, collaborative systems, community systems, social systems, social search, social media, collective intelligence, wikinomics, crowd wisdom, smart mobs, mass collaboration, and human computation (Doan, Ramakrishnan and Halevy, 2011).

Howe (2008) argued that Crowdsourcing existed earlier too, it just that the advent of internet have maximized the reach with more involvement and have offered interactivity. The definition that we consider for our study only concerns the Crowdsourcing through internet, hence the most common and famous example worth considering would be Wikipedia, which is an online portal, ranked 7th globally (Alexa – Wikipedia), written collaboratively by largely anonymous Internet volunteers who write without pay (Wikipedia – About).

Considering the example of Wikipedia, it can be said that Crowdsourcing systems enlists users to „explicitly‟ collaborate to build a long lasting artefact. However, considering this alone would be unfair because there are Crowdsourcing systems where the users ‘implicitly’ collaborate. To explain implicit collaboration, let‟s consider the example of Facebook, world’s biggest online social network with over 750 million users (Facebook – stats), where users are given an option to ‘like’ or ‘report abuse’ various multimedia files, like pictures and videos, and comments. This eases the work of Facebook staff, as it is practically impossible for them to keep track of the enormous content that users generate (Doan, Ramakrishnan and Halevy, 2011). So, instead of Facebook keeping a track of unparliamentary content, the users do it.

Hence, if the user does not have a problem with the content then neither does Facebook. This provides us with the basis of classifying Crowdsourcing system, based on the nature of the crowd‟s collaboration, in the project; Crowdsourcing can be classified into two broad categories

Explicit Crowdsourcing Implicit Crowdsourcing (Doan, Ramakrishnan and Halevy, 2011) But this is too broad classification because Crowdsourcing may exists in any sector. The concept of Crowdsourcing is not industry specific; hence this study will not consider this classification. The classification is discussed in detail in the article ‘models of crowdsourcing‘.

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I'm an eCommerce Project Director at an agency in London and a consultant for a number of eCommerce start-ups. I founded Think etc 9 years ago which now lets me share my research and experience with all the interesting brands, people, places and projects that I have been privileged to work with. My work on crowdsourcing was published by Oxford as part of a journal article and I have been obsessing over eCommerce and Magento over the past several years.

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