Why Social Media Analytics Cannot Rely On Machine Learning
Social media has been the main driver of public conversation for the past decade now, with Facebook having been founded in 2006 and the likes of Twitter and Instagram entering the fray in the ensuing years. According to estimates, in 2016, 78% of all Americans used social media – more than 200 million people. Worldwide, the number amounts to some 2 billion.
Social media is essentially the internet in its purest form, a technology that brings people from across the planet together. This probably seemed like a good idea at the time, although it failed to account for the fact that people in groups tend to be stupid. A person is smart. People in groups are dumb, panicky, dangerous animals. And this can be seen daily on newsfeeds on every platform, which have become a dystopian nightmare of hate, mistruth, narcissism and outright stupidity.
People in groups are also easily exploited, something that marketers and businesses recognized from the outset. Having discovered that social media was an extremely convenient way of advertising to a highly engaged mass audience, they set about monitoring and tracking variables to segment them based on a variety of metrics so that they could tailor and target their campaigns to more specific groups. The social media companies also made this easier, using algorithms to learn what kind of content people wanted to see so they could essentially curate their feeds, showing them little outside their existing likes. This has had a variety of negative consequences, entrenching people’s world view and restricting public discourse.
We are now at a stage where this is evolving even further, with AI and machine learning algorithms taking over from human marketers, and in some cases human users. This has strange implications. Go on Twitter now and you have bots liking tweets sent by other bots, retweeting tweets from other bots, an infinite Russian doll of bots engaging with bots to no apparent end. Twitter is a mess of automated tweets sent by people who haven’t even bothered to read them themselves.
This is not to say that AI is not making the job of social media easier for marketers. There are, undeniably, many areas where it is a benefit, particularly in terms of analysis. There are now thousands of channels across multiple devices, making it practically impossible to measure user engagement manually. Every minute, social media users submit over 347,000 updates to Twitter and ‘like’ more than 4 million things on Facebook.
