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Peel back the layers of information about fake news and a deeper truth begins to take shape. But as I discovered, there is no one string to pull.
The real world is nearly impossible to see in this maelstrom of poorly framed stories, incomplete analysis, self-serving content, lies, misinformation, and invisible algorithms held in private by large companies. This is because human minds need to “construct” their own version of reality – and each of us does this within a community of shared experiences and beliefs.
Said succinctly, there are many social worlds and each is built on its own version of what is real and true. Structures have a profound influence on what gets seen, how it is shared, and who sees the same things.
We came together as a rag-tag team* – a data scientist, a complexity researcher, a visual artist, and a cognitive linguist – to unpack the deeper truth about fake news. What we found is striking. Even more striking to realise that only by gathering a huge amount of data was it even possible to trace this hidden world of conflicted meanings.
No wonder everyone is confused about what the hell is going on!
*The team included Federico Cruz, Mehul Sangham, Lucila Sandoval, and myself.
Our team took a unique dataset of 60 million tweets referencing the US election on Twitter during the week following its completion (November 8th to the 13th). This was a global media conversation that spanned at least 74 countries. We used visualisation software to create images of the relationships throughout this massive web of information. The graphic below was generated from this dataset. The colours represent webs-within-webs for each meshwork of tweets that connect with each other in some way.
Our first analysis was to mine through the data for all the tweets about “post-truth” and “fake news” – to see who was talking about these topics and what they were saying. What we found was that two very different conversations were taking place. The post-truthers were mostly elite media commentators engaging in discussion about each other’s coverage, and themselves.
Contrast this with the fake news aficionados who were mostly grassroots groups and independent media outlets, including a large number of Trump supporters, who actively criticised the “establishment” media as untrustworthy and unreliable. These people were much more prone to trust information from authoritarian sources aligned with their worldview than the “authoritative” sources like scientific expertise or official media outlets.
This disconnect between two very different conversations offers a critical insight – that the very different conclusions people are drawing from failures in the media can be mapped to their modes of sharing and the networks they are embedded in. The liberal-minded critics saw a failure of establishment media to present the facts reliably while the conservative-minded critics saw a failure of establishment media to represent their views of the world.
Both had important things to say, yet each was talking past the other. While the “fake news” critics seek to undermine the credibility of science by elevating their own authority figures, the “post-truth” critics argue that more people should trust the real media, so that we return to rational thought.
What neither camp represents is the system-level observation that these conversations are not about the real issues. Both are distractions that fail to take into account the historic activities that gradually corrupted the media, elections, trade agreements, tax policies, and much more, in the last 40 years.
There has been propaganda for centuries. Misinformation campaigns are not new. What is new is the decentralisation of media creation that enables each community to remain isolated and separate. Also new are all of the digital data trails that make this ecosystem of information something that can be studied in detail.
Why does this matter?
Humanity is dealing with major crises like global warming, the sixth mass extinction, extreme inequality, political corruption, and an economic system built on greed and short-sighted wealth hoarding. So why is it that so many of us keep getting caught up in the celebrity worship of politicians in the top 0.1% wealthiest people on Earth?
If we were to somehow measure the total amount of attention that humans are giving to topics they care about, how much would be on the systemic threats to our civilisation? To what extent would the focus on celebrity culture (including political candidates and electoral races) be a distraction from what is really important?
You can see a taste of this problem in this graphic:
It is like the digital ether has become a giant invisible platform for distracting us from what is really going on. Perhaps even more frightening is the observation that no-one seems to be in control of it. The graphs displayed above show us how profoundly decentralised and emergent the meaning-making process is in today’s media environment. Without ongoing sense-making, analysis and visualisation of the data, we will not know what is really going on.
Take as an example, this pattern that we discovered:
When we drilled into the data, we saw that many conversations are disjointed and don’t overlap with each other. Individual people can have as much influence on the information that spreads as the “official” media outlets. One lesson we can learn from this is that stories can come from anywhere that resonate with the feelings people have in the moment.
Another lesson is that the facts-on-the-ground don’t really matter. People share what feels true to them, and now they have communication tools to organise around. Those of us working to tackle the global threats to humanity must cut through the many layers of meaning to make sense of things ourselves. Then we’ll have even more challenges to communicate what we discern about reality once we’ve done this.
Bringing this back to the main point we started with: the conversation about “fake news” and living in a “post truth” world is not one conversation, it is many. And all of it is a distraction. Practicing discernment is more important than ever. We all have to wade through the deluges of data to see the webs of community dialogue. This requires vigilance and a healthy dose of scepticism. It also requires collaboration among people with diverse backgrounds.
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Our team was able to see the significance of these patterns because we had a data scientist working with a visualisation expert (finding patterns that are conveyed as visual stories); a linguist who has studied political discourse (to make sense of the worldviews and social values distinguishing one from another); and a technology strategist trained in social complexity (helping to bridge changing media landscapes and emergent capacities for truth-interpretation by these different groups).
What we all need to do now – collectively as a species – is build the institutional capacities to make sense of big data on a regular basis. Having a biased meshwork of corporate media outlets won’t be sufficient. Neither will the “democratised” independent people in the grassroots who have shown us how biased they can be in their own worldviews as they interpret the world to serve themselves. The deep truth about fake news is that a great deal of moral integrity and analytic skill is needed to make sense of the world in our complex media environments today. These cultural capacities are desperately lacking today.
This is about connecting the dots, revealing system-level patterns and searching for root causes. It is about collaborating across perspectives to make sense of a complex social world. The analysis we share here is meant to convey just how richly complex this kind of work will need to be in the future. We have merely scratched the surface of what is needed, moving forward.