In 2015, Instagram star Essena O’Neill very publicly declared that she was quitting social media. Her announcement was met with skepticism. People suggested the act of quitting itself was a publicity stunt, as it generated media attention for her and her move to embrace her “real self”. Perhaps this is because we already know that social media represents a curated idea, and not our “real selves”.
Being hyper positive on Social Media is an issue worth pondering. One positive Facebook post on your feed will elicit someone else (on average) to have two more positive posts on theirs. This creates a competition where everyone wants to present their best selves all the time. Highlighting the best moments of our lives can create the illusion that we're not supposed to talk about the negative aspects of life or the moments where we're emotionally down. It can also lead one to be anxious about not being able to keep up with other people's achievements.
“As important as it is to celebrate our highs, it is as equally important for us to acknowledge and talk about our lows.”
Our awareness to the perception versus the reality of our social media lives has become a theme in satirical pop culture. You may have seen the parody video on Instagram husbands, the men who are present with their spouses only to capture photos of them while doing things, social media personas (and ratings) have also been a darker theme on the satirical science fiction show Black Mirror, and most recently Matt Spicer’s feature directorial debut Ingrid Goes West chronicles a woman’s growing Instagram obsession pushing her further into psychosis.
In the book Everybody Lies Seth Stephens-Davidowitz shows how data from Google searches can reveal some humbling facts about who we really are. These searches are our technological ID (our instinctual desires, embarrassing questions, darker curiosities). Here we are our most uncurated selves, and Stephens-Davidowitz refers to this data as “digital truth serum”. In his chapter on social media he juxtaposes this search data against the data collected from social media, making the case that data reveals “Digital Truth” (searches, views, clicks, and swipes) and “Digital Lies” (Social media posts, likes, and dating profiles). Take the stats he provides on two magazines; The Atlantic Vs. The National Enquirer. Google data reveals a one-to-one ratio of searches, indicating people seek out the two magazines equally. Facebook data is strikingly different though, with twenty-seven “Likes” for The Atlantic for every one Enquirer “Like”. When we know people are watching we adjust our behavior (and twist the data) accordingly.
Social pressure assists in maintaining order and civility in societies and “digital truth serum” reveals the many flaws hiding under that civility. The Google data of Everybody Lies is unfiltered and the truth unfiltered can be an ugly thing. A map of the U.S. with the largest numbers of racist searches broken down by state, data that reveals parents are more likely to do searches concerning their daughter's appearance than their sons and that with searches concerning intelligence the gender results are reversed, and the fact that during the economic downturn that started in 2007 searches such as “my mom beat me” or “my dad hit me” shot up.
These are unpleasant things to face; that the U.S. is not as over its racial divides as the narrative during Obama’s two terms would imply, that we still subconsciously value attractiveness in our daughters more than intelligence, and that despite hopeful stats from Children’s Services it appears more children were in fact being abused during the recession.
Stephens-Davidowitz tells of people coming up to him after lectures to let him know that it’s all very interesting, and very depressing. We lie on social media to hide our ugly side, and our ugly side is really ugly. What are the benefits of this “interesting but depressing” data? From a marketing perspective Davidowitz points out that companies have learned we lie online not just to others, but to ourselves, and these companies adjusted accordingly.
Netflix originally allowed users to create a queue of movies they wanted to watch in the future and then later it would remind them of these movies. The data revealed users were filling their queues with movies but they rarely clicked when reminded. Why? Because they were filling them with serious dramas and documentaries. Then watching comedies or romance movies. Netflix stopped asking people to tell them what they wanted and built a model based on data their customers were “most likely to view”. We lie to ourselves based on social standards as well. We tell ourselves we want to watch content that challenges us and makes us think, but for the most part we want distraction. Netflix recognized this, and adjusted their service to reflect our real desires.
From a more personal perspective, being aware that our Facebook Friends lives are probably not as great as they appear could help to reign in FOMO. We have less to fear when we know that we really aren’t missing out on much. Take, for example, this great chart taken from Stephens-Davidowitz’s book. This healthy dose of reality data should console anyone questioning if their relationship is comparable to their friends.
And as for the charting of racist searches, the superficial concerns parents have for their daughters Vs. their sons, and the desperate searches of abused children during the Recession? This data is more than ”depressing”. We now know on a state by state basis where diversity and education is needed, we can make parents aware of their subconscious gender bias, and Stephens-Davidowitz was contacted by child protective service agencies when his data on child abuse was published. He is now helping them track parts of the country where there may be more abuse than what they are recording. These are all positive results provided by data. We are now able to provide solutions for problems society often doesn’t want to acknowledge simply because we now have evidence of their existence. And the potential here can be seen in the success law enforcement agencies have had using data. For example, when Memphis Police began using the data driven Blue CRUSH system (a system utilizing statistics and mapping) the crime rate went down 30%. Search data provides insight into human nature and can help us zero in on social problems. Which is a key first step in being able to solve them.
Antidotes to Understanding Digital Behaviour:
Know that social media is loaded with sins of omission, exaggeration, and outright lies. And don’t base your expectations of others on it
The data on Google searches can be disheartening at times but this has positive potential. It can be used to identify areas in need of education and analyzing the best ways to reach others