  Online communication channels, especially social web platforms, are rapidly
replacing traditional ones. Online platforms allow users to overcome physical
barriers, enabling worldwide participation. However, the power of online
communication bears an important negative consequence --- we are exposed to too
much information to process. Too many participants, for example, can turn
online public spaces into noisy, overcrowded fora where no meaningful
conversation can be held. Here we analyze a large dataset of public chat logs
from Twitch, a popular video streaming platform, in order to examine how
information overload affects online group communication. We measure structural
and textual features of conversations such as user output, interaction, and
information content per message across a wide range of information loads. Our
analysis reveals the existence of a transition from a conversational state to a
cacophony --- a state of overload with lower user participation, more
copy-pasted messages, and less information per message. These results hold both
on average and at the individual level for the majority of users. This study
provides a quantitative basis for further studies of the social effects of
information overload, and may guide the design of more resilient online
communication systems.
