As part of the incredible reMap website, which magically enables you to navitage across the information visualizations in the visual complexity website, I found this puzzling visualization of Web domains and influential people in the Tokyo metro system. The job is by the Information Architects office, and does an incredible job of mixing playfulness and serious information display:

Accordingly to a paper this news article discusses on ScienceNOW, newborns are more prone to be women in warmer climates. Less scientifically, one can say the tropics are more feminine than colder places.

In 'The Surprising Power of Neighborly Advice', Gilbert and collaborators examine an intriguing hypothesis: what is the best predictor of your future reaction to an event, your forecast given the event's info or the reaction of someone close in your social network?

Interestingly, they find that the reaction of someone close in your social network is the best predictor. Not surprisingly, they also find that people often think the contrary is true.

Two direct implications come to mind. The first, discussed by the authors, is on how we consider these two predictors to make decisions. The second, not discussed in the paper, is for recommender systems. It suggests recommendation is more effective using information about other people's reaction to events than about a user's stated preferences.