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Disinformation doesn’t care about your facts. Here’s how you can fight back

In 2011, the 9/11 truther Charlie Veitch released a cellphone video renouncing his earlier belief that the terrorist attack was an “inside job.” As David McRaney explained in How Minds Change , the backlash was “swift and brutal.” Veitch was relentlessly harassed and his website was hacked. There were even death threats. Today, corporate leaders face similar backlash in a number of areas,…

Disinformation doesn’t care about your facts. Here’s how you can fight back

In 2011, a former 9/11 truther named Charlie Veitch renounced his beliefs about the terrorist attack being an "inside job." However, he faced harsh backlash, including harassment, website hacks, and even death threats. Today, corporate leaders dealing with issues like AI technology, DEI policies, and controversial actions face similar challenges.

The problem is not a communication issue but a network issue. Modern communication now occurs in multiple information environments, each with its own influencers and echo chambers. To navigate these networks, understanding their power dynamics is crucial.

Power in networks is determined by centrality, which can be analyzed using three measures: degree centrality, closeness centrality, and betweenness centrality. Degree centrality identifies the most connected individuals, while closeness centrality highlights those with the best access to others. Betweenness centrality reveals nodes acting as bridges between separate communities.

Networking power often comes from forming connections beyond one's existing network, shifting the center of gravity and increasing potential influence.

To strategically navigate networks, consider connecting with friends of friends, as they tend to be more influential than random individuals. However, today's networks are not limited to humans; they also include automated accounts or bots designed to manipulate information spread. In the 2016 Philippine elections, a coordinated influence network was uncovered by analyzing relationships among Facebook accounts, pages, and posts.

These networks artificially created popularity and consensus, convincing people that fringe ideas were widely shared, effectively manufacturing influence.

Once a network is influenced by bots, it starts shaping the behavior of real people. They not only share the fake posts but also create their own based on the false consensus the botnet has manufactured. These amplified posts, in turn, encourage more people to engage, perpetuating the cycle. Social media platforms exacerbate this by rewarding content that generates strong reactions.

For instance, a profile of a politically engaged white woman named "Carol" quickly led her down a rabbit hole of hate speech and QAnon-related content, demonstrating the power of network manipulation.

Written by urgent.news from Fast Company's reporting — not their text. Machine-written — it may contain errors, so check the original before relying on it.

Read the original at fastcompany.com →

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