Some research tidbits for Christmas

Over the last couple of weeks a few interesting research items on social psychology and social network analysis have crossed our desks – so we have compiled them into this collection of research tidbits for Christmas.  Enjoy!

In-flight influence

First up, a study that shows how the decisions of people around us influence our decisions, even if we don’t know the people.  This elegant piece of analysis, written up in this working paper and covered by the Washington Post (albeit with a misleading headline) shows how our decisions about whether to purchase in-flight food and drink are influenced by those around us.   Because the study had access to reservations data, it was able to exclude groups travelling together, and control for parameters such as seat choice.

The research found that people sitting near other purchasers were 30% more likely to make in-flight purchases.  If this is the the level of influence that strangers hold over us, how much more is our behaviour influenced by those who we care about?  Answer: in Idiro’s experience, lots.

The same Washington Post article referred to an interesting piece of research demonstrating the power of peer pressure in schools.  Message to all parents: make sure your kids are in classes with people cleverer and more diligent than them.

A link analysis of languages

Multi-lingual Wikipedia editors: which languages?
Multi-lingual Wikipedia editors: which languages?

There are plenty of studies showing how which languages are spoken by the greatest number of people, which languages are economically the most powerful – but which languages serve as the pivots between other, less popular languages?  To put it another way, if you speak a minority language (like Welsh) and want to understand it written in another (e.g. Kikuyu), which other languages are necessary to make the link?  In this case, most Welsh speakers know English, as do many Kikuyu speakers – so the answer is simple: just English.

Quartz published details of an interesting MIT study looking at this in depth, using three data sources: multi-lingual Wikipedia editors, multi-lingual Twitter accounts, and book translations.  The data is displayed in an interactive website but it’s worth watching this video, as it’s a complex enough study.

One can criticise the data sources, of course (for example, the great firewall of China restricts Chinese Twitter usage) but nevertheless it’s a fascinating topic.  Here in  multi-cultural Idiro, the most common hub language is English (of course), followed, we observe, by Russian.

How many friends?

How many people do we have contact with through our mobile phones?  Idiro’s researchers took a week’s worth of connection data from a European mobile phone network, and counted the number of different phones that each person had contact with over a week.  We then plotted the distribution of the number of contacts each phone had – in other words, the total number of links per person.  As the graph shows, a number of phones were (as one would expect) used rarely or not at all that week.  A few users made over sixty unique connections in a week, and a large number of people made between 5 and 15 connections.  We compared Christmas with an average summer week. and found – no surprise – that people make more connections over Christmas week, as we renew old friendships.

Distribution of the number of mobile contacts per person
Distribution of the number of mobile contacts per person

Finally, here is a study by Hill and Dunbar demonstrating that Christmas card networks are (or were, when we used to send Christmas card to all our friends) a reasonable approximation of Dunbar’s number – 150.

Merry Christmas to all, from the Idiro team

Sex, teenagers and Big Data

A good friend said to me recently that Big Data and analytics is a bit like teenagers and sex; everybody is talking about it but very few are actually doing it. I think he may need to update his knowledge of teenage behaviour but I got his point nonetheless.

 

The rush to Big Data has the usual hallmarks of other past industry hot trends i.e. lots of hot air and hype. Additionally, there are a lot of definitions of what Big Data actually is and what differentiates it from, say, your bog standard Oracle BI/data warehouse.

So what’s my definition of Big Data? If pushed I’d say something similar to the following: “Big Data is the discipline of analysing vast volumes of structured and/or unstructured data with a view to generating insights and predictions that improve business performance”  (OK, I know that’s not very inclusive of non-business activity but you get the general idea).

My gripe about some soi-disant Big Data companies is that all they have done is moved their dashboard reporting tool to Hadoop (if even that). I can understand the temptation to rebrand an existing BI tool as a Big Data platform but it would be unfortunate if anyone actually fell for that.

Here in Idiro we like to differentiate between BI and predictive analytics – there are many companies offering BI tools of varying levels of sophistication. However, there are far fewer suppliers of predictive analytics platforms  (and even fewer still who provide predictive social network analysis like ourselves). In essence, BI tells you what did happen (i.e. after the horse has bolted) and predictive analytics tell you what will happen (while the horse is still happy in the barn). A smart company will use both.

But back to the definition of Big Data…some would argue that Big Data is all about analysing unstructured data such as blog postings, tweets and other such rubbish. Sorry, yes, I know there is useful information in there but there’s a lot of junk too. We prefer not to discriminate against data and believe that any data can form the input for a Big Data platform.

A word of caution lest anyone think that by installing some Big Data platform that all their problems will be solved. The analytics generated by any such platform need to be used to change business behaviour – this is probably the biggest challenge to the successful deployment of analytics within a company. Often there is political resistance within a company to the use of analytics that makes the Israeli-Palestinian problem seem like a walk in the park. Simply put, people and processes need to change if a company is going to capitalise on its investment in analytics.

As for the aforementioned teenagers, I think that when it comes to the adoption of behaviours that they find “beneficial” they exhibit a lot more openness to change than some large companies who desperately need to reinvent themselves. Big Data may or may not be a panacea for all a company’s problems but, once we step away from the buzz and the hype, what we see is that companies small and large, who intelligently leverage analytics for business really do get the edge over their competitors. Call it Big Data, call it analytics, the important thing is to call it right.

Aidan Connolly
Email: a.m.connolly@idiro.com