  Online social networks have transformed the way in which humans communicate
and interact, leading to a new information ecosystem where people send and
receive information through multiple channels, including traditional
communication media. Despite many attempts to characterize the structure and
dynamics of these techno-social systems, little is known about fundamental
aspects such as how collective attention arises and what determines the
information life-cycle. Current approaches to these problems either focus on
human temporal dynamics or on semiotic dynamics. In addition, as recently
shown, information ecosystems are highly competitive, with humans and memes
striving for scarce resources -visibility and attention, respectively. Inspired
by similar problems in ecology, here we develop a methodology that allows to
cast all the previous aspects into a compact framework and to characterize,
using microblogging data, information-driven systems as mutualistic networks.
Our results show that collective attention around a topic is reached when the
user-meme network self-adapts from a modular to a nested structure, which
ultimately allows minimizing competition and attaining consensus. Beyond a
sociological interpretation, we explore such resemblance to natural mutualistic
communities via well-known dynamics of ecological systems.
