Misinformation, spread by exploiting our eagerness to share content without thinking, has created a “new world disorder” that we need to safeguard against
Claire Wardle / Scientific American : Tweets: @coyneoftherealm , @dgwbirch , @carnage4life , @jenlschwartz , @sciam , and @monaelswah Tweets: James C.Coyne / @coyneoftherealm : Currently conversations about social media literacy have a paternalistic framing that the public simply needs to be taught how to be smarter consumers of information. https://www.scientificamerican.com/ ... @dgwbirch : This is why we can't have an Edwardian democracy in a world of social media. One of them has to change. https://www.scientificamerican.com/ ... Dare Obasanjo / @carnage4life : I'm reminded of the dueling trending topics when Epstein died blaming Trump then the Clintons. At first people blamed bots but when Twitter investigated the hash tags were being shared by real users. Easier to blame bots or Russians than concede humans are gullible & cliquish https://twitter.com/... Jen Schwartz / @jenlschwartz : If you want context for Chinese disinformation efforts in the Hong Kong protests, start here. I was thrilled to have online manipulation expert @cward1e write about disinformation for our special issue on Truth, Lies & Uncertainty. https://twitter.com/... Scientific American / @sciam : Digital disinformation is not just about Twitter bots. Our willingness to share content without thinking is being exploited by bad actors to sow division and spread chaos. https://www.scientificamerican.com/ ... @monaelswah : “Ahead of platform moderation, they are relabeling emotive disinformation as satire so that it will not get picked up by fact-checking processes. In these efforts, context, rather than content, is being weaponized. The result is intentional chaos.” https://www.scientificamerican.com/ ...
Context & Ripple Effects
Claire Wardle's Scientific American argument landed in August 2019, just before the period it seemed to predict: her claim that casual, unthinking sharing — not just botnets or trolls — drives what she calls a 'new world disorder' framed misinformation as a human-behavior problem rather than a platform-engineering one.
The coverage that followed stress-tested that frame. Within months, pandemic, protest, and election disinformation had split the US public, with 'Plandemic' as the case study of network failure; a global industry of PR firms selling fake accounts and pseudo news sites industrialized what Wardle described as organic carelessness; and by 2021 researchers found fact-check labels on Trump tweets correlated with wider spread — evidence that the intervention layer was being absorbed into the very feedback loops it targeted.
First-order effects
- The named vector shifts from anonymous bad actors to ordinary users: every share decision becomes part of the distribution system, which puts the burden on platforms to design against reflexive amplification rather than only against malicious originators.
- Fact-checking infrastructure itself comes under pressure — labels meant to correct content become signals that attract attention, forcing Twitter and its peers to reconsider whether visible moderation marks help or hurt.
Second-order effects
- A commercial supply side emerges around the vulnerability: the disinformation-services industry documented by BuzzFeed turns Wardle's 'eagerness to share' into a purchasable product line of fake accounts, false narratives, and pseudo news sites, pricing influence like any other marketing service.
- Bad actors adapt faster than moderators — relabeling emotive disinformation as satire to evade fact-checking, and resurrecting already-debunked content through Wayback Machine links after deletion, so each enforcement action spawns an evasion technique.
Third-order effects
- If the pattern holds, information integrity stops being a content-moderation function and becomes core platform infrastructure — trust systems designed into feeds and ranking rather than bolted on as post-hoc labels, with regulators increasingly treating distribution architecture, not individual posts, as the policy target.
- The paternalistic 'teach users to be smarter consumers' framing James Coyne criticizes gives way to structural approaches, because the record shows educated audiences still share first and verify later when the content is emotive enough.
The trend: Misinformation is evolving from a user-literacy problem into an arms race over platform trust infrastructure, where every moderation tool gets reverse-engineered into a distribution tactic.