  In this study, we build on previous research to understand the conditions
within which the Wisdom of the Crowd (WoC) improves or worsens as a result of
showing individuals the predictions of their peers. Our main novel
contributions are: 1) a dataset of unprecedented size and detail; 2) we observe
the novel effect of the importance of the unimodality of the social information
shown to individuals: if one does not see only one clear peak in the
distribution of the crowd's predictions, the WoC is worsened after social
exposure; and 3) we estimate social learning weights that we use to show that
there exists individuals who are much better at learning from the crowd and can
be filtered to improve collective accuracy.
