One thing that all the top social data experts we work with at The SI Lab have in common is their unwavering intellectual curiosity. Here’s a rundown of four of my favourite books if you want to stay curious too…
At some point, you’ve probably heard that top CEOs read on average of 60 books per year. If you attended university you were probably told to “read around your subject” too. A commitment to lifelong learning appears to be essential for success in the professional world too.
But, how do you ‘read around’ when it comes to social data analysis?
I’d argue that you don’t need to focus on the practice of social data analysis, but rather the areas surrounding it. By widening your peripheral reading, you’ll be able to fill in the missing gaps that you didn’t realise were there. And, in doing so, you’ll know more about different subjects and how they fit together – really important when you’re interpreting human behaviour from data.
Tips to get started:
- 1. Read more than the key books on reading lists [well, apart from this one]. I see so many ‘must read’ lists that concentrate solely on the main topic, such as data or marketing – not the thinking around the topic.
- 2. Find the links between your subject and another field. Personally, I read a lot of books on behaviour, psychology and neuroscience, and economics. I rarely pick up a book that’s just about data.
- 3. Don’t think ‘answers’, think ‘questions’. Stay curious about what the theories and stories being discussed are, and question how they can make your analysis more powerful.
With that in mind, here are four books that changed how I think about social data analysis. Each of them helped me to create new practices to make my analysis more rigourous and insights more insightful.
Decoding the Irrational Consumer
- How to commission, run and generate insights from neuromarketing research
- Darren Bridger
If you’ve been looking to dip your toe into the neuromarketing pond but been apprehensive about understanding complicated theories then this is the book for you. Written in a conversational style, it is a must read for those looking to do more with understanding consumers’ non-conscious and applying those insights to marketing.
You’ll be taken on a journey through theoretical insights on the irrational consumer [and debunking some myths], then into different research tools, you can use to get neuro-insight, and finally how to put it all together. There’s nothing on social data here but there are many insights that you can “borrow” for your own work.
So, how does this apply to social intelligence? Inspiration on the focus of your analysis and metrics that you could be used to optimise content. I personally love the whole book but one thing I use most often in content creation is the implicit memory webs. How to use social data to understand your customers’ implicit associations and linkages to a brand, product or service, and how this can be used to optimise your content.
Take those mattresses-in-a-box (you’ve probably been chased down by them online at some point). In a book I wrote last year, I found that because the mattresses contain memory foam people naturally associate them with being too hot. Why? Because memory foam mattresses of old were apparently too hot. This natural association creates a barrier to purchase that mattress-in-a-box brands must overcome.
- How social networks can make us smarter
- Alex Pentland
Pentland believes that the effects of digital social networks and other similar technologies create a disconnect between traditional ideas about society and the current reality. He argues:
“to understand our new, hyperconnected world, we must extend familiar economic and political ideas to include the effects of these millions of digital citizens learning from one another and influencing one another’s opinion. We can no longer think of ourselves as only individuals reaching carefully considered decisions; we must include the dynamic social effects that influence our individual decisions and drive economic bubbles, political revolutions, and the internet economy”
That’s social physics. And it can be made reality from big data. It’s not just social data, but social data does play an important role.
Out of the four books, this is the closest to your own work in social data analysis. Here you’ll find more about how patterns of interaction can translate into intelligence through the flow of information and engagement – and a lot about understanding human behaviour from data. It also goes to show that you’re working in an interdisciplinary practice which combines knowledge from a range of fields.
I loved the story at the start of the book about financial day traders sharing tips on a social networking site. In an unconventional but scientific recommendation, the ideas and tips shared on the network were intentionally slowed down to overcome ‘herd behaviour’ of the traders. By slowing the spread of ideas in the financial day traders social network the traders doubled the average return on investment. Clearly a concept you won’t find in your usual management handbook, who wants to stop the spread of ideas? This story gets you hooked at the start with its unconventional wisdom.
- Face and Interpretation in the Age of Information
- John D. Caputo
Hermeneutics is the theory that “everything is a matter of interpretation”.
This can be a pretty hard going read as you have the history of hermeneutics through the ages and their link to religion and law, with a lot of philosophical debate woven in. For instance, you’ll explore theory in relation to the many philosophers researching and arguing it.
From the four books, Hermeneutics is the furthest stretch from your work. But some interesting questions arise from it. Alternative facts make a play early on, and the discussion around the role of hermeneutics in AI is interesting – it ultimately argues that we need humans to interpret data.
You can’t use technology to generate insight – that’s what you are for! For example:
“the central issue in contemporary AI work…. We know how to build machines today, sleek and shiny, miniaturised, even hand-held machines, dazzling, digitalised information-machines that can perform amazing feats at breathtaking speed that are slowly beginning to make human beings look bad. We know how to build machines that follow the rules – but we are at a loss to build machines that do not”.
Caputo questions how we can programme machines to do the unprogrammable – to interpret? He believes that in such situations robots are stupid.
One of the key things that I took from this book was the idea of “deconstruction”.
Deconstruction is the black sheep of the hermeneutics world, but it puts the focus back on how things are heard and understood, how they are perceived and interpreted.
I created a method of “deconstruction” to start the segmentation process for social data analysis. It starts by segmenting what is known and then finding the unknown; unknowns from the data that cannot be categorised. It also places importance on how consumers perceive and interpret brand experiences.
- Nils. J. Nilsson
This is a great little book that came about from Nilsson’s work in artificial intelligence from asking a simple question, “how do people come to know things?”
Almost in answer to Caputo’s observation in Hermeneutics that we need to make machines do the unprogrammable, Nilsson’s work looks into beliefs as our core knowledge of the world and how they guide our actions and decisions.
The book argues that:
“our beliefs play important roles in perceiving a current situation, in identifying appropriate actions, and in predicting the effects of these actions.”
In our social data analysis world, they help us to explain what we observe. We’re all prone to bias in our interpretations and this inherently comes from our beliefs and experiences. By understanding how we come to get beliefs and how to evaluate them is important, especially when you are continually analysing other people’s beliefs.
This has impacted my work in various ways but let’s talk about how it plays into setting up your research and communicating your insights.
When we analyse social data, you, your client, your colleague or your boss will have a ‘gut feeling’ or assumption about what you’re going to find. This can impact the way you analyse the data – you seek to confirm the hypothesis and may fall into the confirmation bias trap.
Beliefs also play an important role in how we share the insight. I don’t know about you, but I’ve found about 90% of the time the customer has a slightly different belief about a brand than what the brand holds about itself. That is a tough nut to communicate to someone who holds completely different thinking!
Reading More, Seeing More
In every book I read, I always find links to my work. Even in fiction novels. My books are tattered, have loads of folded pages and marked with a million notes – because I’m continually questioning. You don’t ever want to borrow a book from me…
And, the best thing about reading more? According to a study by ScienceDaily, “when we read, the brain doesn’t make a real distinction between reading about an experience and actually living it”. We get both new experiences and new ways of thinking.
Do let me know if you dip into any of my must reads…. And, do share you’re reading list too.
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