  Crowdsourcing has revolutionized the process of knowledge building on the
web. Wikipedia and StackOverflow are witness to this uprising development.
However, the dynamics behind the process of crowdsourcing in the domain of
knowledge building is an area relatively unexplored. It has been observed that
an ecosystem exists in the collaborative knowledge building environments (KBE),
which puts users of a KBE into various categories based on their expertise.
Classical cognitive theories indicate triggering among the knowledge units to
be one of the most important reasons behind accelerated knowledge building in
collaborative KBEs. We use the concept of ecosystem and the triggering
phenomenon to highlight the necessity for the right mix of users in a KBE. We
provide a hill climbing based algorithm which gives the ideal mixture of users
in a KBE, given the amount of triggering that takes place among the users of
various categories. The study will help the portal designers to accordingly
build suitable crowdsourced environments.
