Blog 1: Connected

Reading the book Connected by Christakis and Fowler was a very eye-opening experience.  Never before did I image how interconnected we were to those around us.  I had previously heard that we were all connected to one another with at most six degrees of separation, but unaware of the level or impact of these connection.  According to the third degree rule, we significantly affect one another through three degrees of separation, with the effect getting weaker the more distant the connection.  This means that a friend, a friend’s friend, and a friend’s friend’s friend will all affect one another in tangible ways.  This influence persists even if the more distant friends never interact with one another directly.  To highlight this point, as it pertains to the social network below, Liz can affect Allen and Allen can affect Lisa, even if Liz and Lisa never have direct contact, she can affect her through indirect connections.  Moreover, the connection is a two-way street.

Image result for social network nodes

While simplistic, this transfer of influence can persist on a larger scale depending on the distance of nodes from one another and transitivity (Christakis and Fowler 2010, Social Network Sensors for the Early Detection of Contagious Outbreaks).  Distant connections, ones with few mutual ties, can serve as bridges allowing influence to reach new networks of connections.  In the picture above this could be Allen’s connection to Liz, allowing him to affect the highly transitive (many mutual connections) network on the left.  Increased transitivity allows members of the network to influence one another more readily.  In the case of a pathogen, if Allen was a carrier of a virus and exposed Liz, Liz could infect Emma and Shane.  Once Emma and Shane are infected, because of their high transitivity, the rest of their network could be infected.  This allows us to understand how pockets of disease can form, similar to what happened in Rockdale, GA.

Detailed interview transcripts:


network visualization of the outbreak

Other examples in the book used to illustrate connectivity include social network effects on patterns of obesity, voting, and smoking.

The insights gained from our study of social networks can be operationalized to help detect and prevent disease. Christakis and Fowler mentioned how vaccines could be targeted to highly connected individuals, at a central  hub of a network, to increase herd immunity versus immunizing the entire population.  This concept is shared by others. (Eubank et al.  2004, Modelling Disease Outbreaks in Realistic Urban Social Networks) Nodes that serve as a central hub can be used to detect the incidence of disease in a population. Targeting such individuals may also help in programs trying to change the behavior of a populations: criminals that regularly go in and out of jail could be more effectively persuaded to change their ways if people at the central hub demonstrated an aversion to crime or modified their own behavior.

Our discussion thus far has focused more on strong network connections but weaker connections also have a tremendous impact.  Weaker connections allow for the passage of information between transitive networks.  For this reason, weaker connections often are the source of new employment opportunity because they provide new information.  It has also been found through the study of the creators of musicals that a group with highly transitivity, coupled with more distant connections (providing different perspectives),  allows for the emergence of greater creativity as a whole increasing the  probability of success for the newly created musical.

Leave a Reply