37. Is it hot in here or are we in South Carolina?

Hi friends,

Welcome to the thirty-seventh dispatch of How Humans Flourish, a research-informed newsletter on how humans thrive.

This month, we’re reading New York Times Bestseller Dataclysm: Love, Sex, Race, and Identity–What Our Online Lives Tell Us about Our Offline Selves by data scientist and technology founder Christian Rudder. 

Last week, I introduced the concept that social networks act as powerful amplifiers of contagions, thanks to their structure and connectivity. Contagion in this context refers to how behaviors, emotions, or conditions spread through networks much like infectious diseases. In simpler terms, it’s the way that what individuals do, feel, or experience can ripple through their social circles, amplifying and accelerating the spread of various phenomena.

Rudder provides a compelling illustration of this by describing an experiment by MIT students that used Facebook data to create a “gaydar” tool. This software, trained on known profiles, could predict a man’s sexuality with 78% accuracy just by analyzing his social connections. 

78% is pretty impressive considering there are still ongoing public conversations debating how many gay people exist. Some studies say the percentage is as low as 1% of the population, others as high as 15%. 

Sexuality, unlike race, isn’t always visually obvious. Without external indicators like wearing rainbow flags, it’s challenging to discern someone’s sexual orientation just by looking at them. This invisibility is why terms like “gaydar” exist: they’re attempts to uncover hidden aspects of identity.

But why is this important? Rudder highlights a fascinating application of data from statistician Nate Silver, who applied his renowned poll-modeling techniques to same-sex marriage ballot initiatives. By aggregating data and analyzing trends, Silver’s work provides a snapshot of public opinion and predicts how these attitudes might evolve. Interestingly, this analysis correlates with self-reported data from Gallup about the percentage of people identifying as gay in various states. The correlation suggests that in more accepting states, higher percentages of people report being gay. This implies that, in states with less acceptance, the true number of gay individuals might be higher than reported, hidden due to societal pressures.

An interesting thing about Silver’s work is how it relates to another data source: what people in each state told Gallup about their own sexuality. Here are those self-reported numbers graphed against Silver’s most current projections for the acceptance of gay marriage, state-by-state. Rudder has coded each state by its legal treatment of gay marriage and labeled a few of the outliers, as well.

He writes, “On the horizontal, you see that, per Silver, Mississippi is the least tolerant state and Rhode Island is the most. On the vertical axis, Gallup’s numbers range from 1.7 percent in North Dakota, to 5.1 percent in Hawaii. And, as you see from the slant of the trend line, the more accepting a state is of homosexuality, the higher its self-reported gay population. Remarkably, if you walk that dotted line out to 100 percent support of gay marriage (statistically imagining a future world of perfect tolerance), you find it implies that roughly 5 percent of the population would say they are gay, absent social pressure not to be…

If you accept this independent estimate of 5 percent, arrived at using three of the biggest forces in modern data—Nate Silver, Google, and Facebook, with an assist from that standby of old-school polling, Gallup—you begin to see those self-reported numbers in a different light. When Gallup tells us that, for example, 1.7 percent of North Dakota are gay, then perhaps something like 3.3 percent of the state is gay and unwilling to acknowledge it. In New York, about 4 percent of the population is openly gay, leaving maybe 1 percent gay and silent. And likewise for every state. Against the steadiness of the data, the ups and downs in self-reported gay populations take on a new meaning: it shows a nation of Americans leading secret lives.”

The implications are significant. For example, health practitioners are well aware HIV is most often spread by self-identified heterosexual men who engage in same-sex encounters. The highest rates of transmission, as seen below, are in the South.

Rudder notes that in the U.S., searches starting with “Is my husband…” most commonly end with “gay.” 

He writes, “‘Gay’ is 10 percent more common in such searches than the second-place word, ‘cheating.’ It is 8 times more common than ‘an alcoholic’ and 10 times more common than ‘depressed.’”

He continues, “Those questioning searches are most common where repression is at its highest: South Carolina and Louisiana, for example, have the highest rates, and acceptance of gay marriage is below the national average in 21 of the 25 states where this search is most frequent.“

Aside from being more at risk for certain transmissible diseases, there’s ample quantitative evidence linking anti-LGBT laws to increased depression and suicide rates among men who have sex with men. In fact, a recent study conducted in Poland saw a 16% rise in suicide rates following the enactment of such laws.

OkCupid asks the question below solely to its self-identified heterosexual users. The responses show 51% of women and 18% of men have had or would like to have a same-sex experience. These figures far exceed estimates of the gay population, suggesting that sexual fluidity is more common than rigid categories might indicate.

Which brings us full circle. Social networks play a crucial role in shaping our lives and the lives of those around us—regardless of whether they know they are in a network or not.

With gratitude,

P.s. Unfortunately, the Kindle version of my book doesn’t include page numbers, so I’m unable to reference specific pages.