My colleague Johan Bollen and his colleagues have been working on a project that tries to measure and verify the “happiness paradox,” which is an extension and elaboration of the “friendship paradox.” From the MIT technology review:
The friendship paradox is straightforward to explain. It comes about because of the skewed way people collect friends on online social networks such as Twitter and Facebook. Most people have a small number of friends—a few dozen or so. But a tiny fraction of people have huge numbers of friends millions or tens of millions of followers in some cases.
This has two effects. First, it makes them much more likely to appear in a random person’s list of friends. And second, it dramatically skews the answer when calculating the average number of friends that a person’s friends have.
Bollen et al then explain the analogous happiness paradox:
Bollen and co begin by analyzing the most recent 3,000 tweets sent by some 40,000 Twitter users. They use a standard algorithm to analyze each tweet to determine its sentiment—whether positive or negative—and then assume this gives a sense of the user’s happiness level. In other words, they assume that people who are less happy send more negative tweets. They also include in the analysis the number of followers and followees for each individual.
The results make for interesting reading. Bollen and co say there is clear friendship paradox at work in this network, as expected. But they also say there is a less striking but nonetheless significant happiness paradox at work, too.
Indeed, Bollen co say their evidence suggests that the more unhappy the individual, the stronger the happiness paradox they face. “Although happy and unhappy groups of subjects are both affected by a significant happiness paradox, unhappy subjects are most strongly affected,” they say.
The original paper is here. Recommended.