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The Attention Tracker

Wikipedia hype curves, aligned by days to release

The free pre-release tracking charts everyone used to argue about went private in 2025, and nothing free replaced them. This page is not a resurrection — nobody here polled anyone. It is the next honest thing: how many humans opened each upcoming film's English Wikipedia article, every day, lined up by days-to-release so a film ninety days out is compared with other films when they were ninety days out. An instrument, not a crystal ball — the footer says exactly what it can and cannot tell you.

Free, no account. Films join automatically from the release calendar — run the odds on them when the curves make you curious.

The numbers behind the curves (last 14 tracked days)

How to read it

Lift is each film measured against itself: a day's pageviews divided by that film's own median daily pageviews across days 90 through 60 before release. A franchise starts famous and an original starts obscure; lift ignores the head start and shows acceleration — a trailer drop makes the same shape spike either way. Raw views shows the absolute audience, where the log scale is the only honest way to put a 400,000-view day and a 900-view day on one chart. Hollow points are single-day spikes past ten times a film's trailing week — bot filtering upstream is imperfect, so they're marked, not trusted. Gaps in a line are days the source had no data; nothing here is interpolated, ever.

What this measures. The Attention Tracker measures daily human pageviews of each film's English Wikipedia article (Wikimedia Foundation pageviews API, bot-filtered, records since July 2015), aligned by days-to-release against comparable films. It is a behavioral attention proxy — not survey-tracked awareness, and not a box-office forecast. Big-film curves are more reliable than small-film curves.

What it doesn't claim. The published research is blunt: attention proxies added only marginal predictive power over what production budget and theater count already predict (Goel et al., PNAS 2010), and the one Wikipedia study that worked (Mestýan et al., 2013) worked mostly for big films, with theater counts inside the model. Read these curves as what the market is looking at, never as a number a film will open to. Normalization, exactly: lift = a day's pageviews ÷ that film's own median daily pageviews over days 90–60 before release; films without at least 7 days of that window get no lift curve rather than a fabricated one.

Data: Wikimedia Foundation pageviews API, refreshed daily. Films come from the release calendar; articles are matched and verified against Wikidata, and article renames are stitched, never dropped. Free, no account. Nothing on this page is investment advice.