Platform Health Metrics > Iffy Quotient

Calculating the Iffy Quotient

For more information on our methodology and findings, download our White Paper.

For more complete explanation of the process, and some reflections about limitations of this measurement process, see our report.

How Many Sites are Unclassified by Media Bias/Fact Check?

Media Bias/Fact Check has not investigated every site. Sites that do not appear on any of the MBFC lists we classify as "Unknown", neither "Iffy" nor "OK". If MBFC doesn't keep up with new sites, over time we would mistakenly misclassify more and more of the truly Iffy sites as unknown. To check for that possibility, the graphs below track the fraction of unknown URLs.

Comparison with Other Classifiers

Media Bias/Fact Check makes judgments according to its own criteria. The Open Sources project provides an alternate list from which we can also compute an Iffy Quotient. The graphs below compare the Iffy Quotient as computed using the MBFC and Open Sources lists.

If you have an alternative source list, or an automated classifier that we could use classify sites as Iffy or OK, please contact us.

Engagement-Weighted Iffy Quotient

As a supplementary analysis, we also compute an engagement-weighted version of the Iffy Quotient. Rather than treating all popular URLs as equal, we weight them by the estimated engagement scores that NewsWhip provides us. The denominator, then, is the sum of engagement scores for the top 5,000 URLs, and the numerator is the sum of engagement scores for those URLs that are from Iffy sites.

A comparison of the Iffy Quotient based on URL counts vs. engagement scores.


For some interpretations of how the Iffy Quotient has changed over time at Facebook and Twitter, download our White Paper.


To be alerted when there are meaningful changes in the Iffy Quotient for either Facebook or Twitter, sign up for our email alerts.