Select-to-classify or scan any page for propaganda techniques: intent-colored highlights, entity framing, and a role-map overlay.
Users
7
0 in 30 days
Rating
0.0 / 5
unchanged in 30 days
Ratings
0
0 in 30 days
Store rank
#222K
#186K among extensions
Version
1.0.0
updated 10 Jul 2026
Users
monthly, 3 months
Latest, 15 Oct 2026:7 usersMove the mouse over the chart for any month
Ratings count
monthly, 3 months
Latest, 15 Oct 2026:0 ratingsMove the mouse over the chart for any month
The Chrome Web Store rounds user counts down to the leading digit, so the user line moves in steps. The ratings count is exact and is the better signal of real adoption.
About CN1C
CN1C brings propaganda-technique detection to any web page. Select text and click the CN1C
button, or scan a whole article, to see:
- A verdict (propaganda / neutral) with confidence
- The coarse intent behind the text (e.g. distort reality, shift blame, delegitimize opponent,
manufacture consent, confuse & distract)
- The exact spans of text driving that classification, highlighted inline in the page, color-coded
by intent
- Entity framing — who's cast as protagonist, antagonist, or innocent, with a live role-map overlay
connecting each entity on the page to its role
Powered by an XLM-R multi-task model developed at the Quality & Usability Lab, TU Berlin, as part of
the CN1C research project (a continuation of "Check News in 1 Click", EACL 2024). Multilingual:
English, German, French, Italian, Romanian, Russian, Ukrainian.
By default, analysed text is sent to the CN1C model server at checknewsin1.click for classification.
When the CN1C model finds no propaganda, a research LLM at the GWDG Academic Cloud cross-checks the
verdict so that topics outside the training data are not missed. You can point the extension at a
different model server (including one running on your own machine) in the popup settings. See the full privacy policy at https://checknewsin1.click/privacy.html.
This is a research prototype. It is strongest on Russia–Ukraine-war-related news text; general text
is out of distribution for the current model.