Recognizing Foreign Interference
Goodbit · April 25, 2026 · 3 min read
Goodbit engagements combine short game-based learning with AI-moderated conversation and measurement. Participants first respond to claims or scenarios, then talk through what surprised them, what felt credible, and what they would repeat. The results below combine those layers: what people knew, what shifted, what held, and what the conversations revealed.
At a glance
- 2,055 Canadians completed a foreign-interference engagement in December 2025.
- Effect size was 1.42 on participants' comfort expressing concerns about foreign interference.
- Recognition of confusion as a manipulation goal rose from 37% to 54%.
- Recognition of emotional exploitation tactics rose by 6 to 10 points, depending on content type.
- Among participants who started with low confidence, 82% improved.
- 55% improved on willingness to discuss across political lines.
- 80% recognized diaspora communities as victims of foreign interference, not threats.
- 37% improved on the diaspora-as-victim measure.
- Post-game survey completion was 26%, so targeted gains should be read alongside that limitation.
Summary
Foreign interference is not only a problem of false information. It is a problem of social interpretation. Manipulative campaigns try to make people confused, suspicious, and less willing to talk across difference. They often work by exploiting real grievances and turning uncertainty into distrust.
In December 2025, Goodbit ran a digital engagement with a national Canadian sample of 2,055 participants. The campaign tested whether a short experience could improve recognition of foreign-interference tactics while strengthening the social conditions needed to resist manipulation.
The engagement produced large gains in recognition and targeted gains in social confidence. It also helped participants understand diaspora communities as targets of foreign interference rather than sources of threat.
Methodology
Participants completed a 25-claim true-or-false game focused on content laundering, narrative manipulation, cross-border destabilization, emotional exploitation, and the role of diaspora communities. The campaign was designed to teach tactics without turning the subject into a warning about any single community or political side.
The measurement layer included pre/post questions and recall measures across four categories: recognition of interference tactics, willingness to engage across political difference, understanding of collective resistance, and interpretation of diaspora communities in the context of foreign interference.
The campaign also examined completion and response patterns. The post-game survey completion rate was 26%, a limitation that should be read alongside the strength of the observed shifts.
Findings
Recognition of manipulation improved. The share of participants who could identify confusion as a manipulation goal rose from 37% to 54%. Recognition of emotional exploitation tactics rose by 6 to 10 points, depending on content type.
Social confidence moved most clearly among participants who started with low confidence. Eighty-two percent of low-confidence participants improved. Fifty-five percent improved on willingness to discuss across political lines. Among low-confidence participants, 53% improved on collective-resistance and regional-understanding measures. The overall population moved less cleanly on that measure, so it should be read as a targeted-segment gain rather than a universal confidence lift.
The diaspora finding was especially important. By the end of the engagement, 80% of participants recognized diaspora communities as victims of foreign interference, not threats. Thirty-seven percent improved on the diaspora-as-victim measure.
That distinction is not a side issue. A campaign about foreign interference can backfire if it increases suspicion toward communities that are themselves targeted by interference. In this campaign, the engagement improved recognition while preserving the distinction between threat actors and affected communities.
The conversations showed why this matters. Many participants described having sensed that something was wrong in the information environment, but not having the language to name it. Once they could distinguish confusion from persuasion, manipulation from disagreement, and targeted communities from perpetrators, the issue became easier to discuss without collapsing into accusation.
Methodology portability
This case study shows that Goodbit can help institutions measure whether an intervention increases public resilience without creating collateral harm. For foreign interference, that distinction matters.
The work is not only to teach people that manipulation exists. It is to help them recognize how it works, where it attaches to real social tensions, and how to talk about it without making those tensions worse.
Goodbit measures both sides of that problem: recognition and social consequence.
About Goodbit
Goodbit is a Canadian engagement and measurement platform for understanding how people think and talk about contested issues. We combine short game-based learning, AI-moderated conversation, and campaign analytics to reveal where information lands, where trust breaks down, and what makes people more willing to engage.
Contact: hello@madebygoodbit.com
Goodbit · April 25, 2026