This TED talk from Nicholas Christakis explores how social networks can be applied to understand many aspects of people’s lives. To illustrate this point, Christakis shows that close network ties with people who are obese increases someone obesity risk by 45%. The effect scales up to 3 degrees of separation. This means that people you may not even know or even interact with my have an impact your physical health – i.e. if a friend of a friend of a friend is obese, your risk of obesity is 10% higher than that expected by random chance. Christakis points the the underpinning phenomenon of homophily – birds of a feather flock together. For obese people, it could be that people of a similar body size tend to communicate or that people that have a common exposure to a certain health plugs communicate with one another. Further, if your friend adopts a behavior, the chances that you adopt that behavior too are much higher.

Listen to the full talk HERE.

John Bohannon of Science News reports on a recent study by Yury Kryvasheyeun, a research at Australia’s National Information and Communications Technology Research Centre of Excellence in Melbourne.Kryvasheyeun’s team demonstrated that twitter data collected during Hurricane Sandy in 2012 can be a better predictor of damage that FEMA’s models for a fraction of the cost. Their predictions were robust even accounting for confounding factors the millennial bias of twitter users and the existence of twitter bots. This approach to data analytics could be a major step in the modernization of fast and effective disaster relief efforts. Kryvasheyeun hopes to scale up the potential of social media in this realm by incorporating a richer Facebook data set.

Read the full article HERE.

Check out this Superbowl 50 Twitter data interactive created by Luis Natera of cuidadpixel. Interestingly, Lady Gaga trends higher than either team that participated in the game. Natera highlights the differences between the people who tweet about artists vs about athletes as well as the powerful reach of advertisements for companies like Doritos and Esurance.

You can play around with the interactive HERE.

NOTE: The original article is written in Spanish. If you are not a Spanish speaker, we recommend using Chrome to view the article in order to take advantage of the translation feature.

Rafi Letzter of Tech Insider reports that Facebook Messenger has a feature capable of sending information about when other users are online to your computer in plain text. Soren Louv-Jansen used this to write a program that checked Facebook every ten minutes and recorded these timestamps. With that data, he could tell when his friends put turned on their phones in the morning and logged off at night, resulting in a database of his friend’s sleeping schedules. This news is particularly interesting in the wake of Lab Director, Noshir Contractor‘s recent article in PLOS One “Circadian Rhythms in Socializing Propensity.” His team found that the time-of-day that people use social media has a significant effect on the connections the forge. Though most people socialize online in the evenings, the most meaningful communications and friendships occur late at night, when not many people are awake. The research suggest that the presence of oxytocin at that point in the human circadian cycle encourages this deep bonding.

Read the full Tech Insider article HERE.

Read Noshir’s full article HERE.