  Online traces of human activity offer novel opportunities to study the
dynamics of complex knowledge exchange networks, and in particular how the
relationship between demand and supply of information is mediated by
competition for our limited individual attention. The emergent patterns of
collective attention determine what new information is generated and consumed.
Can we measure the relationship between demand and supply for new information
about a topic? Here we propose a normalization method to compare attention
bursts statistics across topics that have an heterogeneous distribution of
attention. Through analysis of a massive dataset on traffic to Wikipedia, we
find that the production of new knowledge is associated to significant shifts
of collective attention, which we take as a proxy for its demand. What we
observe is consistent with a scenario in which the allocation of attention
toward a topic stimulates the demand for information about it, and in turn the
supply of further novel information. Our attempt to quantify demand and supply
of information, and our finding about their temporal ordering, may lead to the
development of the fundamental laws of the attention economy, and a better
understanding of the social exchange of knowledge in online and offline
information networks.
