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Spreading the Smiles: Happiness in large social networks

A commonly understood phenomenon, people who surround themselves with happy people tend to be happy themselves. We usually see the opposite: a college student randomly paired with an unhappy roommate tends to be unhappy for the time they live together. This is on a short term, but how does association with happy people affect people in the long term? Can happiness spread and leave lasting impressions for years?

The British Medical Journal published James H. Fowler and Nicholas A. Christakis’s research on a case study they conducted over 20 years of the Framingham Heart Study social network. They studied 4739 individuals between 1983 and 2003, looking for the influence of surrounding oneself with happy people. Fowler and Christakis looked into the spread of happiness between people and if clusters form within social networks due to this phenomenon.

Defining “happiness” as positive emotions and looking at people who were continuing participation with a Framingham Heart Study, the researchers asked the subjects to rank their feelings during the week on a numerical scale. Previous connections between the people varied; some of them knew only one other before the study while some had up to eight friends in the group. Fowler and Christakis created a network of the subjects as they began in 1983 and applied the Kamada-Kawai algorithm to generate network images across the years with minimal crossing ties. This visualization (below) shows the progression of the subjects from 1996 to 2000.

Progression of the subjects from 1996 to 2000

At the end of the 20 year study period, the researchers found noticeable clusters of happy and unhappy people in the network. Specifically, they found that a person increases his chances of being happy by 25% with a happy friend who lives within a mile of him. Overall, happiness can be considered a “collective phenomenon” which spreads with connected people over time.

 

Source: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2600606/

 

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