How Facebook "Likes" Reveal Your Most Intimate Secrets

bernardmarr
Bernard Marr Founder and CEO, Advanced Performance Institute

Posted on June 14th 2013

How Facebook "Likes" Reveal Your Most Intimate Secrets

Did you know that your 'Likes' on Facebook could expose intimate details about you as well as personality traits you might not want to share with anyone? Some things about ourselves we rather keep private, right? Most of us don’t openly share with the World sensitive personal attributes such as our sexual preferences, our religious or political views, how intelligent we are, how happy we are with life or whether we consume alcohol, cigarettes or even drugs.

However, a recent study shows that it is possible to accurately predict a range of highly sensitive personal attributes simply by analyzing the ‘Likes’ you have clicked on Facebook. The work conducted by researchers at Cambridge University and Microsoft Research shows how the patterns of Facebook ‘Likes’ can very accurately predict your sexual orientation, satisfaction with life, intelligence, emotional stability, religion, alcohol use and drug use, relationship status, age, gender, race and political views among many others. It is quite scary that those “revealing” ‘Likes’ can have little or nothing to do with the actual attributes they help to predict and often a single ‘Like’ is enough to generate an accurate prediction.

Facebook privacy

Who would have thought that a ‘Like’ for ‘Curly Fries’ is a strong predictor of high intelligence? Maybe this is a good place to reveal that I love curly fries (never thought I would share this publicly). Anyway, here are some of the most predictive ‘Likes’ identified in the study:

  • For high intelligence: Curly Fries, Science, Mozart, Thunderstorms or The Daily Show
  • For low intelligence: Harley Davidson, Lady Antebellum, Chiq and I Love Being a Mom
  • For Satisfaction with Life: Swimming, Jesus, Pride and Prejudice and Indiana Jones
  • For Dissatisfaction with Life: Ipod, Kickass, Lamb of God, Quote Portal and Gorillaz
  • For being emotionally unstable (neurotic): So So Happy, Dot Dot Curve, Girl Interrupted, The Adams Family and Kurt Donald Cobain
  • For being emotionally stable (calm and relaxed): Business Administration, Skydiving, Soccer, Mountain Biking and Parkour
  • For being old: Cup Of Joe For A Joe, Coffee Party Movement, The Closer, Freedomworks, Small Business Saturday and Fly The American Flag
  • For being young: Body By Milk, I Hate My Id Photo, Dude Wait What, J Bigga and Because I Am A Girl
  • For being gay (males): Kathy Griffin, Adam Lambert, Wicked The Musical, Sue Sylvester Glee and Juicy Culture
  • For being straight (male): X Games, Foot Locker, Being Confused After Waking Up From Naps, Sportsnation, WWE and Wu-Tang Clan

The thing is, when we click ‘Like’ we want to show our friends on Facebook that we feel positive about or supportive of specific online content such as status updates, photos or products, books, music or other individuals such as celebrities. What many of us don’t realize is that by doing so we openly share information about ourselves that can then be used to predict other, more personal, attributes that we would not want to share so openly. We now live in a world where everything in digitalized – were we consume music in digital formats, read eBooks, where we shop online and interact with friends and colleagues using social media platforms. This also means that we leave a digital trail of our life and our preferences, which in turn can make it easy to figure out our attributes and personality traits. We call this type of analysis ‘Big Data Analytics’ and it allows us to use large volumes of data – such as Facebook ‘Likes’ – and turn them into insights and predictions.

Predicting personality traits and attributes is nothing new and was around before 'Big Data Analyics'. For example, personality questionnaires have been around for a long time and they do accurately predict personality types and traits. However, what was different in the past is that we had much more control over the process – we had to complete the survey or give others permission to use our data. With Facebook ‘Likes’ it is slight different because they are by default publicly available. This means that the information you reveal by clicking on a ‘Like’ button can – by default – be used or ‘exploited’ by others, for good causes and bad ones.

Commercial companies can use this type of Big Data Analytics to dynamically customize the ads you see on your Facebook page (or in fact anywhere) based on your personality traits. Just think of an online ad for the latest car – for people that are classed as shy, reserved and married the ad might highlight safety and family friendliness, while for an single, outgoing and active person it might highlight the attractive design and sporty drive. More worryingly, Governments could (and do) use this type of analysis to identify our political views and how they are shifting. Insights from this can then be used to target election campaigns etc.

One problem is that these predictive models are not perfect (no model ever will be). Not everyone who likes curly fries is automatically highly intelligent. The danger is that we use the insights from predictive modeling and label people wrongly or come to incorrect conclusions about them. I can imagine simple mobile phone apps that would allow you to predict personality traits of your friends. Would you like that? Do you feel that this type of analysis invades your privacy? Will you think twice about ‘Liking’ anything on Facebook from now on? Let me know what you think…share your views…

And as always, feel free to connect via TwitterLinkedIn or The Advanced Performance Institute.

bernardmarr

Bernard Marr

Founder and CEO, Advanced Performance Institute

Bernard Marr is a global enterprise performance expert and a best-selling business author. He helps companies to better manage, measure, report and analyse performance. His leading-edge work with major companies, organisations and governments across the globe makes him an acclaimed and award-winning keynote speaker, researcher, consultant and teacher. Bernard is acknowledged by the CEO Journal as one of today’s leading business brains.

He has written a number of seminal books and over 200 high profile reports and articles on enterprise performance. This includes the best-sellers 'Key Performance Indicators', ‘The Intelligent Company’, ‘More with Less’, ‘Managing and Delivering Performance’ and ‘Strategic Performance Management', a number of Gartner Reports and the world’s largest research studies on the topic. His expert comments regularly feature in high-profile publications including The Times, The Financial Times, Financial Management, the CFO Magazine and the Wall Street Journal.

He has worked with and advised many of the world’s best-known organisations including Accenture, Astra Zeneca, Bank of England, Barclays, BP, DHL, Fujitsu, Gartner, HSBC, Mars, Ministry of Defence, Microsoft, Oracle, The Home Office, NHS, Orange, Tetley, T-Mobile, Royal Air Force, SAP and Shell, among many others.

He currently focuses on helping clients to:
- create strategic performance frameworks
- develop relevant and meaningful KPIs and metrics
- develop business analytics and 'big data' strategies
- develop management dashboards and reporting solutions 
- train and coach teams to become ‘high performance organisations’
- align people management practices with strategic performance objectives
- understand the emerging trends of big data analytics

His engagements range from executive awareness and training sessions right through the design and implementation of corporate performance management and reporting approaches. Bernard can be contacted at bernard.marr@ap-institute.com

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Comments

JRMigs
Posted on June 14th 2013 at 3:36PM

Thankfully, I add ample random 'likes' because I am human.   Years ago, Blockbuster asked me to build models predicting what people would buy based mostly on their video-rental history.  We always need to take these exclamations with a grain of salt.  Given that I see the excellent offers posted on my very active facebook news feed - either this does not work as well as claimed - or I am just too random for my own good (adds).  Nevertheless, I would love to participate in an effort to learn and improve the 'likes' analysis.   @jrmigs

Heaven Jelo
Posted on June 17th 2013 at 7:17AM

Thanks for sharing the thought.. I really had a great time reading it and it opened my mind..

 

elizabeth.hyde
Posted on June 20th 2013 at 5:57PM

Interesting. I agree it needs to be taken with a grain of salt, as I "like" Harley-Davidson (and ride one), but I also "like" Mozart, thunderstorms, Einstein, Shakespeare, and science; and dislike the Daily Show and fries in general, not just curly ones. 

Seshu Madabushi
Posted on June 20th 2013 at 10:35PM

I am just curious about the profiling based on the likes - what about the random likes that you do just because your friends have liked NYT or Morning Show (sponsored stories from Facebook). Apart from that what about the requests you get just because your aunt has opened a business, has a facebook page now and wants to build her fanbase. The third component is that what about businesses asking its customers to like (as a marketing person to the restaurant industry I always ask my clients to request likes from their customers).

Given that a person likes a page/brand for reasons unknow it is very difficult for me to digest the fact that just because I like curly fries I am an Einstein now..