Over the past month or so, the drumbeat of ominous news about Facebook and how its user data have been used (or misused) by the social platform and customers such as Cambridge Analytica has been never-ending.
To hear the hyperventilating of reporters, you might think that Facebook was teetering on the brink of an implosion or similar corporate catastrophe as a result of all the nasty revelation.
Well … maybe not so much.
Securities firm Raymond James has surveyed a sample of ~500 Internet users in the wake of the Cambridge Analytica “user abuse” allegations in an effort to determine just how concerned people are about the news, and how it might be impacting on Facebook usage.
It comes as no surprise at all that a clear majority of those surveyed have concerns about Facebook’s use of their personal data. To wit:
Very concerned about Facebook’s use of personal data: ~44%
Somewhat concerned: ~40%
Not concerned: ~15%
But when asked how they may be changing their use of the social platform as a result of knowing about Facebook’s treatment of their personal data, it turns out that only ~8% of the survey respondents have stopped using (or plan to stop using) the platform.
On the other hand, a solid half of the survey respondents report no changes at all in their use of Facebook – now or in the future.
For those in the “mushy middle,” the majority of them plan to use the social platform “somewhat less” rather than “significantly less” than before.
So, what we’re witnessing is unmistakably heightened user concerns generated by a flurry of news reports that lead to … very little.
In fact, in a report that accompanies the survey findings, Raymond James’ analysts go even further, predicting that user concerns will likely ease as the news cycle slows on this topic.
Considering how strongly Facebook has integrated itself into many people’s daily lives, that prognosis comes as little surprise to me.
But what about you? Have you made changes in your usage of the social platform? Have you noticed changes made by your friends on Facebook? Feel free to share your perspectives with other readers.
It’s human nature for people to strive for the most flattering public persona … while confining the “true reality” only to those who have the opportunity (or misfortune) to see them in their most private moments.
It goes far beyond just the closed doors of a family’s household. I know a recording producer who speaks about having to “wipe the bottoms” of music stars — an unpleasant thought if ever there was one.
In today’s world of interactivity and social platforms, things are amplified even more — and it’s a lot more public.
Accordingly, there are more granular data than ever about people, their interests and their proclivities.
The opportunities for marketers seem almost endless. At last we’re able to go beyond basic demographics and other conventional classifications, to now pinpoint and target marketing messages based on psychographics.
And to do so using the very terms and phrases people are using in their own social interactions.
The problem is … a good deal of social media is one giant head-fake.
Don’t just take my word for it. Consider remarks made recently by Rudi Anggono, one of Google’s senior creative staff leaders. He refers to data collected in the social media space as “a two-faced, insincere, duplicitous, lying sack of sh*t.”
Anggono is talking about information he dubs “declared data.” It isn’t information that’s factual and vetted, but rather data that’s influenced by people’s moods, insecurities, social agenda … and any other set of factors that shape someone’s carefully crafted public image.
In other words, it’s information that’s made up of half-truths.
This is nothing new, actually. It’s been going on forever. Cultural anthropologist Genevieve Bell put her finger on it years ago when she observed that people lie because they want to tell better stories and to project better versions of themselves.
What’s changed in the past decade is social media, of course. What better way to “tell better stories and project better versions of ourselves” than through social media platforms?
Instead of the once-a-year Holiday Letter of yore, any of us can now provide an endless parade of breathless superlatives about our great, wonderful lives and the equally fabulous experiences of our families, children, parents, A-list friends, and whoever else we wish to associate with our excellent selves.
Between Facebook, Instagram, Pinterest and even LinkedIn, reams of granular data are being collected on individuals — data which these platforms then seek to monetize by selling access to advertisers.
In theory, it’s a whole lot better-targeted than the frumpy, old fashioned demographic selects like location, age, income level and ethnicity.
But in reality, the information extracted from social is suspect data.
This has set up a big debate between Google — which promotes its search engine marketing and advertising programs based on the “intent” of people searching for information online — and Facebook and others who are promoting their robust repositories of psychographic and attitudinal data.
There are clear signs that some of the social platforms recognize the drawbacks of the ad programs they’re promoting — to the extent that they’re now trying to convince advertisers that they deserve consideration for search advertising dollars, not just social.
In an article published this week in The Wall Street Journal’s CMO Today blog, Tim Kendall, Pinterest’s head of monetization, contends that far from being merely a place where people connect with friends and family, Pinterest is more like a “catalogue of ideas,” where people “go through the catalogue and do searches.”
Pinterest has every monetary reason to present itself in this manner, of course. According to eMarketer, in 2014 search advertising accounted for more than 45% of all digital ad spending — far more than ad spending on social media.
This year, the projections are for more than $26 billion to be spent on U.S. search ads, compared to only about $10 billion in the social sphere.
The sweet spot, of course, is being able to use declared data in concert with intent and behavior. And that’s why there’s so much effort and energy going into developing improved algorithms for generating data-driven predictive information than can accomplish those twin goals.
Rudi Anggono
In the meantime, Anggono’s admonition about data mined from social media is worth repeating:
“You have to prod, extrapolate, look for the intent, play good-cop/bad-cop, get the full story, get the context, get the real insights. Use all the available analytical tools at your disposal. Or if not, get access to those tools. Only then can you trust this data.”
What are your thoughts? Do you agree with Anggono’s position? Please share your perspectives with other readers here.
An article by technology author Steve Lohr published last week in The New York Times caught my eye. Titled “How Privacy Vanishes Online,” it explores how conventional notions of “privacy” have become obsolete over the past several years as more people engage in cyber/social interaction and web e-commerce.
What’s happening is that seemingly innocuous bits of information are being collected, “read” and reassembled by computers to build a person’s identity without requiring direct access to the information.
In effect, technology has provided the tools whereby massive amounts of information can be collected and crunched to establish patterns and discern all sorts of “private” information.
The proliferation of activity on social networking sites such as Flickr, Facebook and LinkedIn is making it easier than ever to assemble profiles that are uncanny in their accuracy.
Pulling together disparate bits of information helps computers establish a “social signature” for an individual, which can then be used to determine any number of characteristics such as marital status, relationship status, names and ages of children, shopping habits, brand preferences, personal hobbies and other interests, favorite causes (controversial or not), charitable contributions, legal citations, and so on.
One of the more controversial experiments was conducted by MIT researchers last year, dubbed “Project Gaydar.” In a review of ~4,000 Facebook profiles, computers were able to use the information to predict male sexual preference with nearly 80% accuracy – even when no explicit declaration of sexual orientation was made on the profiles.
Others, however, have pointed to positive benefits of data mining and how it can benefit consumers. For instance, chain grocery stores can utilize data collected about product purchases made by people who use store loyalty cards, enabling the chains to provide shoppers relevant, valuable coupon offers for future visits.
Last year, media company Netflix awarded a substantial prize to a team of computer specialists who were able to develop software capabilities to analyze the movie rental behavior of ~500,000 Netflix subscribers … and significantly improve the predictive accuracy of product recommendations made to them.
To some, the Netflix program is hardly controversial. To others, it smacks of the “big brother” snooping that occurred in an earlier time during the Supreme Court confirmation hearings for Robert Bork and Clarence Thomas, when over-zealous Senate staffers got their hands on movie store rental records to determine what kind of fare was being watched by the nominees and their families.
Indeed, last week Netflix announced that it will not be moving forward with a subsequent similar initiative. (In all likelihood, this decision was influenced by pending private litigation more than any sort of altruism.)
Perhaps the most startling development on the privacy front comes courtesy of Carnegie Mellon University, where two researchers have run an experiment wherein they have been able to correctly predict the Social Security numbers for nearly 10% of everyone born between 1989 and 2003 – almost 5 million people.
How did they do it? They started by accessing publicly available information from various sources including social networking sites to collect two critical pieces of information: birthdate, plus city or state of birth. This enabled the researchers to determine the first three digits of each Social Security number, which then provided the baseline for running repeat cycles of statistical correlation and inference to “crack” the Social Security Administration’s proprietary number assignment system.
So as it turns out, it’s not enough anymore merely to be concerned about what you might have revealed in cyberspace on a self-indulgent MySpace page or in an ill-advised newsgroup post.
Social Security numbers … passwords … account numbers … financial data. Today, they’re all fair game.
Over the past month or so, the drumbeat of ominous news about Facebook and how its user data have been used (or misused) by the social platform and customers such as Cambridge Analytica has been never-ending.
Nones Notes 