Digital news consumption has gotten harder to measure
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Illustration: Allie Carl/Axios
It's become nearly impossible to reliably capture what's going viral online, without manually tracking engagement on posts.
Why it matters: The internet was supposed to unleash a new level of transparency around news consumption. But it's more muddled than ever.
- Instead, platforms are hoarding the data to avoid scrutiny over how their algorithms work.
Driving the news: Two weeks ago, Meta officially shut down CrowdTangle — a platform it acquired in 2016 that allowed users to measure the engagement of posts and accounts across social media.
- Originally celebrated as a breakthrough in transparency, CrowdTangle became a liability for Meta when journalists and researchers used it to suggest Facebook's algorithms favored hyper-political content.
State of play: Facebook is far from the only platform that has taken steps to keep insights about behavior on its platform out of view.
- TikTok used to display audience data next to certain hashtags in its videos. But it pulled down that feature after the beginning of the Hamas-Israel war when it argued journalists were misinterpreting the data.
- X, Reddit and other social networks have begun limiting backend access to their data to prevent AI firms from scraping it. That's also made it harder for researchers and journalists to analyze content trends.
- More news engagement has moved to private groups and encrypted chats that are difficult for third parties to measure amid privacy concerns. (Gen-Z is particularly sensitive to posting public information about their personal lives.)
The big picture: Metrics cobbled together from third-party vendors and trending hashtags collectively show a more limited picture of consumer behavior on social today compared to the CrowdTangle era. But search data via Google Trends remains consistent and reliable.
- There are ample ways for news companies to analyze specific articles, but news organizations don't generally share article-level engagement data for image and competitive reasons.
What to watch: There's hope that generative artificial intelligence can help news companies analyze large data sets more easily in the absence of links. But getting access to the right data to analyze in the first place is harder than before.
