The accessibility of means to produce, distribute, promote and consume content fast made it possible for well-organized and funded interest groups to rely on fake news and post-truth fact distribution to decisively influence critical popular votes – Brexit and the US elections among the major events.
Picture this: a person registers a domain, sets up a content site using a free-of-charge WordPress theme and links the domain to the new website. Using the in-built functionality for post publishing, the person starts publishing content – totally fake or filled with alleged facts that don’t correspond to the truth and distort reality.
Since the dawn of the modern internet, there always has been such content – we just didn’t see it as it appeared low in the search results (the best place to hide a dead body is on the second page of the Google results, right). But in 2016 we have Facebook and Twitter. Provided, behind this newly created news site is a well-organized group of “community managers” to push it, the fake news would quickly spread on the social media and generate hits to the original source, resulting in actual consumption of the information. Mission accomplished! The web counters would register the increased traffic and influence the search engines to push the fake news up in the results as their business model is directly dependent on high traffic sites.
The two successful use cases in 2016 – the US election and Brexit, have set a standard: any content that was caring messages vaguely or entirely not corresponding to the truth, but liked and re-shared by a well-organized community on social media was very successful in winning people to a given cause.
Now picture a world where every interest group: political, business, corporate or else that is able to fund a community and content creators, is able to produce and spread fake news to influence people’s decisions about virtually everything – what we eat, what we buy, where we travel, what vaccine we inject into our kids, whom we elect and support, what company we work for, who we send to jail in short – how we distinguish right from wrong, good from bad, pretty from ugly.
If we don’t want to find ourselves living in a complete distortion of reality, we need to accomplish these things:
1. Educate people about how to judge information as truthful or false.
2. Reliably classify fake news as such in near real time.
3. Enable credible fact checking in near real time.
4. Track down bots and trolls that spread fake and untruthful news against payment.
Number One is a joint responsibility of the each and every one of us who thinks that living in a lie will be very damaging for the society – once more education on all societal levels should be combined with a missionary passion.
In theory, tasks Number Two, Three and Four should be best tackled by the main search engines and social media networks. But this is just in theory. Take Google, for example, trying to develop a censoring capability would make them very vulnerable – it would reduce the speed they index the content to make it searchable and would increase immensely the cost of processing of every single post (Google indexes 60 trillion websites as of November 2016). Furthermore, it would not only hurt their bottom line, it would hurt their revenue too by forcing them to take down high interest websites. Twitter and Facebook are in the same situation. Facebook had to cope with a big scandal earlier in 2016 when their editorial team was accused of anti republican biases.
It is imaginable that Twitter would tag facts in a Tweet of Donald Trump with his 18.2 Million followers as false. While there is a chance for Google to enforce some policy by modifying their Page Ranking and thus take a bit of steam out of the high traffic fake news sites, the options for the social networks are very limited.
Social listening solutions have all the means to work out algorithms to track down untruthful content and classify user behaviour and profiles. Being in the space of business analytics, these companies have also the credibility for it and a not restricted by any legislation. It would also boost their business offering and will position them strongly with their clients. The major drawback of the social listening solutions in counterfeiting of fake news is that they rely on external content harvesters to collect online content – 99.9% of these companies serve online content in their platforms, but they don’t harvest and pre-process it. For this, they use 3rd party services. This would vastly diminish their flexibility in working on fast and reliable algorithms for fake news detection as the source and its metadata is outside their analytical control.
The second group of companies that potentially are well set to counterfeit fake content are the content syndicators and aggregators. Reversely, their weak spot is that they cannot connect with the social layer and analyze the content distribution dynamics.
Premium content providers that handle TV, Radio and Print content have the content and are well positioned to take on the fight in their respective area of control. They also lack social and also they need to extend their text analytics capability as their core expertise is elsewhere now.
2017 will be critical in curbing the fake and post-truth trend. We at Sensika are gearing towards playing our part. We are very well-positioned for this as we control the process of content harvest, fusing all possible content types into one place, where we can analyze it efficiently.
But we know this is a huge task for a single company. We need to associate with as many people and organizations as possible that share the opinion that fake and post-truth news poses a huge challenge and shall be zealously opposed.
Please, use the contact form below to get in contact with our team if you want to know more.
Looking forward to a more real and credible 2017.