Every list on TopTrendingPeople is sorted by one number, the trending score. It answers a single question: how much more attention is this person getting right now than they usually do? It is not a measure of fame, talent or approval. This post explains how that number is built and why it moves the way it does. All figures come from our data as of early November 2026.
The short version
The score adds up three parts:
- Spike: how far views of a person's English Wikipedia article on the latest day rose above their normal level.
- Google Trends: how much search traffic Google reported when the person recently appeared in its trending searches.
- Resting: a small amount based on normal readership, so quiet periods are still ordered sensibly.
The first two fade quickly once a moment passes. The third is always small. Together they explain why a lesser-known name having a big day can sit above a household name having an ordinary one.
Part 1: the Wikipedia spike
For every person we track, we store daily views of their English Wikipedia article. From those we work out a baseline: the median daily views over a period that ends at least seven days before the latest reading. The median means one unusual day cannot distort what "normal" looks like. We need at least seven days of data before we calculate a baseline at all.
The spike is the number of views on the latest day above 1.5 times the baseline. If someone normally gets 1,000 views a day, the first 1,500 views on the latest day count for nothing. Only the views beyond that line add to the score.
Why a 1.5x line?
Very famous pages wobble from day to day. A page with tens of thousands of regular readers can swing up or down by a large amount without anything unusual going on. The 1.5x threshold keeps those everyday swings out of the score, so the top of the list is reserved for genuine jumps.
A worked example
As of early November 2026, Nithya Raman had a baseline of about 2,500 daily views. Her latest day came in at roughly 184,600. The calculation runs like this:
- Threshold: 1.5 × 2,497 ≈ 3,750 views
- Spike: 184,633 − 3,746 ≈ 180,900
- Resting: 1% of 2,497 ≈ 25
A handful of extra points from Google Trends brings her to her listed score of about 180,900. Almost all of it is spike: attention jumped to roughly 74 times her usual level.
Part 2: Google Trends
Every 15 minutes we read Google's public trending-search feeds for the United States, the United Kingdom, Canada, Australia and India. Each trending phrase is matched against English Wikipedia, and only phrases whose article describes a person are kept. Google attaches an approximate traffic figure to each trend, and we record it.
The Google Trends part of the score is the peak traffic figure from the last three days, multiplied by 0.5. It then halves every 12 hours after the person last appeared in a feed. A name that drops out of the feeds loses half of this boost within 12 hours and three quarters within a day.
This part matters most for people whose Wikipedia data has not caught up yet. Charlie Woerner, for example, had no recent Wikipedia readings in our data when he appeared in a feed in early November, so his whole score of about 10,000 came from Google Trends.
Part 3: the resting score
Most people are not trending on any given day. Without a third part, thousands of them would all score zero and the order between them would be arbitrary. The resting score is simply 1% of the baseline. It keeps widely read pages above rarely read ones, but it is far too small to compete with a real spike.
Florence Pugh shows how this works. She has one of the highest baselines in our entertainment category, at about 34,000 daily views. Her latest day, about 14,500 views, was below her usual level, so she had no spike. Her score was 340: exactly 1% of her baseline.
Why scores fall back down
The score is built to fade. Three rules stop yesterday's attention from staying at the top:
- Trends decay. The Google Trends boost halves every 12 hours after the last appearance and drops out entirely after three days.
- Stale views decay. Wikipedia publishes each day's views a few hours after the day ends, and we collect them once a day. If a person's latest reading is more than two days old, counting from the end of that day, their spike halves for every further day. A missed refresh cannot pin anyone at the top.
- Hourly recalculation. We recompute every score once an hour, so decay is applied steadily rather than in one daily step.
You can see the effect on Jack Campbell. His latest recorded day shows about 128,800 views against a baseline under 300, but that reading is several days old. His spike has already halved more than three times, leaving a score of about 10,300.
Rising: a related but different question
The Rising pages ask whose readership grew the most in relative terms. Instead of one day against a baseline, they compare average daily views across two equal windows: the latest day against the day before, or, on Rising this week, the latest seven days against the seven before.
Two filters keep these lists meaningful:
- A person needs at least 500 average daily views in the earlier window, so tiny pages cannot top the list on noise.
- The later window must be at least 1.2 times the earlier one, which screens out ordinary wobbles.
In the seven-day comparison as of early November 2026, Gardner Minshew went from about 540 average daily views to about 23,000, an increase of roughly 4,100%. Deb Haaland rose from about 840 to about 27,900.
What the score does not tell you
The score measures attention, not its cause. A jump can follow a new film, a match, an election, an anniversary or any kind of news, and the numbers look the same either way. We do not label why someone is trending. Each person's page links to recent headlines from news publishers, so you can read the coverage yourself. For more on our sources and their limits, see the About page.
