How Big Data is Affecting Social Media in 2019

Over the last few years, social media has changed the way we interact with the world. Many of us use it as the primary method of staying in touch with friends and family, of sharing our personal experiences with our peers, and of establishing some sort of online presence.

Just as social media influences us, though, we influence social media – and it’s all thanks to the types of data we share online.

As well as firing off witty tweets and posting images of our fancy brunches on Instagram, many of us interact with brands online. We also share our opinions on what we like or don’t like. We make our political opinions known to practically anyone and everyone who bothers to go looking for them. Without even thinking about it, we provide so much data about ourselves every time we share a Facebook post, or watch an Instagram story, or click through to an ad on Twitter.

And, of course, we readily share some of our most basic information any time we link up our social media profiles to any sort of associated app or programme – our age, our gender, our location. It’s all there, just waiting for a data scientist or analyst to find it.

How this shapes your online experience

One of the primary ways in which big data analytics affects the way people use social media is, of course, advertising.

Even the least tech-savvy of social media users will probably have noticed by now that they tend to get adverts and promotions from brands they follow on social media, or at least from companies that would most likely appeal to a lot of people in their peer group.

The interactions (or lack thereof) with these adverts then acts as a further source of big data for those companies, and allows them to better understand their audience – what they respond well to, which demographics are most valuable, etc. From there, businesses can collate their findings and create test audiences, meaning that social media users may find themselves receiving adverts or posts that have been designed to apply to their niche interests.

In a non-commercial context, too, social media has become a much more tailored experience. Machine learning has allowed artificial intelligence to implement algorithms which direct social media users to other pages and resources that align with their interests; perhaps a similar musician to one they already follow, or a blogger that hashtags their images with ones the user has already shown interest in.

What the future holds

By 2020, it is predicted that the accumulated volume of big data will reach 44 trillion gigabytes. This incomprehensible amount of data will prove to be invaluable in terms of digital marketing, and will no doubt continue to shape the social media experience into one that is tailored to each specific user.

We can’t say for sure, of course, but it seems likely that social media platforms will continue on the same trajectory over the next few years, and carry on evolving into an online maze of content, commerce, and – what it was originally designed for – social interaction.