The Washington Post and ProPublica analyzed Facebook group posts that disputed election results:
To determine the extent of posts attacking Biden’s victory, The Post and ProPublica obtained a unique dataset of 100,000 groups and their posts, along with metadata and images, compiled by CounterAction, a firm that studies online disinformation. The Post and ProPublica used machine learning to narrow that list to 27,000 public groups that showed clear markers of focusing on U.S. politics. Out of the more than 18 million posts in those groups between Election Day and Jan. 6, the analysis searched for words and phrases to identify attacks on the election’s integrity.
The more than 650,000 posts attacking the election — and the 10,000-a-day average — is almost certainly an undercount. The ProPublica-Washington Post analysis examined posts in only a portion of all public groups, and did not include comments, posts in private groups or posts on individuals’ profiles. Only Facebook has access to all the data to calculate the true total — and it hasn’t done so publicly.
Read more about the methodology behind the analysis.
Tags: facebook, insurrection, machine learning, ProPublica, Washington Post
