Social media platforms, such as Facebook and Twitter, have become more than just arenas for people to share thoughts and communicate. They have become the go-to portals for accessing the latest news, political reports and entertainment gossip. However, the spreading of untruthful information, of fake news, is becoming increasingly prevalent, and the nature of social media data makes it incredibly easy for these untruths to reach those audiences who are most likely to accept them as fact and react exactly as intended.
In the South African context, for example, we have seen the social media battles between forces aligned to the Gupta’s, such as Black First Land First, and journalist Alex Hogg.
What’s interesting about this fake news dissemination, however, is how targeted and, therefore, effective it was. Similar scenarios that shift narratives from real matters to petty – but sensitive – gripes have been played over and over again across the world, from the Trump campaign to Bell Pottinger. Fake news is rife and audiences are playing right into the hands of those responsible.
So, what role does big data play in the dissemination of fake news? In addition to this, how do we differentiate between what is real and what is not? Lastly, how can we leverage big data to generate a time line, or news feed, that gives us legitimate news and not hyped-up, agenda-driven nonsense?
Big Data’s role in social media
Sites like Facebook structure your feed based on data collected from your interests, link clicks, and even the friends you have. Your feed is unique to you, and what you see may not necessarily appear in the time lines of your friends or anyone else. A single comment on a post will automatically signal your interest in similar posts, and you will receive more of them based on the sites internal algorithms.
You build the narrative you receive, without even realising it, and the content of your timeline becomes your truth, even as the content of another’s becomes theirs. As humans, we tend to cling to our beliefs, and believe anything that supports our own beliefs over those of another. It’s easier to accept something as truth if it supports an idea we already own.
Activist groups, politicians and even companies are using this to their advantage. For example, a fast food group can pick the most advantageous audience by targeting the time lines of people who have expressed an interest in similar foods. Likewise, political parties can stir up dissent and rally supporters by deliberately disseminating news that paints them in a positive light, however indirectly. Thus, fake news is borne and we accept it unquestioningly.
Awareness and avoidance
The trouble with fake news it, well, that’s it’s fake. It is hard to differentiate between truth and lies when the lies are so easy to accept. This is an inherent issue with data analytics on these platforms. To turn the tide and stem the flow of fake news distribution, people need to take action themselves.
People need to start being highly aware of what they post on social media, whether sharing a post, commenting on one, or even reacting. The site, The Internet Knows Where Your Cat Lives, perfectly illustrates just how much data people are giving out to the world without even realising it. It’s time to be smarter.
For organisations, this can be detrimental, unwittingly opening up security gateways for unauthorised access to company information. Conversely, organisations who are leveraging big data to target audiences need to strike a balance between what is acceptable and what is crossing the line. Governance policies around data use can go a long way to ensuring that target audiences are reached without being, well, creepy.
By Gary Allemann, Managing Director, Master Data Management