Social media behaviours – modelling, and why we need to free the data
Understanding behaviours can be based on theoretical models, or based on data. In the best cases, data validates a model. We believe this is key to delivering the promise of an era of mass consumer empowerment in which the cost (wifi and mobile plans), technology (phones) and platforms (social and web) gives all of us the potential to be heard, seen and influence our societies. Understanding those behaviours is how we help brands, content creators and people close the gaps between them, to all derive more value out of a unique period in human history.
What do we (as OneFifty) need to be able to identify these models and put them into practice?
Solid academic insight (often from across fields as diverse as psychology, economics, history, and natural science).
Industry-leading experience – from creating some of the best-known social media functions in major businesses, to being awarded social creators, to elite sports performance. We bring together experience of what drives the social ecosystem from a surprising range of perspectives.
Utilising large-scale data from digital and social platforms to analyse, predict and validate behaviours
It’s the final aspect I’m keen to address in this post. It is integral to the improvement of how the ecosystem works to have real data to show actual behaviours. It is this which moves us on from a world in which an unrepresentative group of generally well-meaning individuals in a select few enclaves of London, New York and LA stick their finger in the air and confidently assert ‘what people want’ (I love Mad Men as much as anyone, for the record). It does a disservice to the opportunity presented by the social ecosystem, and it’s bad for businesses, creators and consumers.
This post outlines in the first few paragraphs how Google has restricted, consistently and over an extended period, the volume of data available for analysts to use (the rest of the post is about SEO, so don’t read further down it if you’re not interested in that world).
Google aren’t alone in that. Most platforms offer an API (basically an automated way to interact at scale with a social network, for those with a less technical mindset), which allows one to extract information. Twitter’s is arguably the most comprehensive for these purposes. Facebook have a phenomenal one, but limit certain dimensions you’d love to use. Instagram has a pretty limited one for this purpose, whilst Snapchat essentially has nothing. LinkedIn literally doesn’t. (Note APIs have other purposes, and I’m rating them on a top line level, and for social data analysis purposes only).
Why does this matter? It creates gaps in our potential understanding. Not insurmountable ones, but ones which increase the amount we infer or correlate, which decreases certainty. For some groups who heavily use certain platforms it may even create blind spots. Some of the reasons are understandable – this sort of system costs money to build, and the benefits are external. But as with lighthouses, a classic case of positive externalities in economic theory, the benefits are enjoyed by third parties. However, the availability of this data has systemic benefits which, I’d argue, ultimately rebound to the benefit of the social platforms, increasing understanding, adoption and commercial use.
What am I arguing for? In essence, it’s a consistent and public call to arms from those who use this data, to assert its value, and encourage social platforms and digital ecosystem partners (like Google) to make more data available and more openly. There are issues incumbent on the community of users to self-police, to prevent abuse (there’s a very good reason Google have cracked down on SEO, for example, which has long been plagued by a section of its denizens using underhand tactics), but it remains the right thing to do, just as the open source movement has benefitted all those across the computer science and technology world.
If we don’t have as much social data as possible, as freely available as possible, we risk missing out on huge benefits for business, social creators and everyday people. It’d be like restricting ink supply to the flourishing printers world of early modern Europe: regressive and ultimately counter-productive.