Follow-for-Follow Amplification Networks: Misinformation on California Voting Process
Authors: Katie Jonsson, Netta Wang, Isabella Garcia-Camargo, Stanford Internet Observatory
Research: Daniel Bush, Abuzar Royesh, Stanford Internet Observatory; Andrew Beers, University of Washington's Center for an Informed Public
Earlier this week, EIP analysts were tracking a low-engagement, cross-platform misinformation narrative regarding vote by mail processes in California. The analyst team took special interest in this case study as the tweets were part of a large network of “follow for follow” pro-Trump meme accounts. In this case, a Twitter account claimed that California voters will be turned away at the polls unless voters manually change their voting method preferences online due to California Gov. Gavin Newsom’s May vote-by-mail executive order. In May, in response to COVID-19 concerns, Newsom did issue an executive order to send each California voter a ballot by mail. However, voters will not be turned away at their polling stations, even if they do not manually change voting preferences online. Voters can bring their blank mail-in ballot to the polls to receive an in-person ballot, or show up empty-handed and receive a provisional ballot. The EIP has classified this as procedural interference as the post is misleading information about the actual election procedures.
A tweet from a now-suspended account that spread misinformation about voting processes in California. The body of the tweet tags 20 other twitter users, a common practice in follow-for-follow accounts.
This narrative received low (1-10 reactions, comments, shares) to medium (10-500 reactions, comments, shares) engagement across Facebook and Twitter. The above tweet was retweeted more than 80 times within two hours of posting. While this was the first tweet that our analyst team identified, we do not rule out the possibility that earlier tweets shared the same misinformation. The EIP identified seven more tweets gaining traction and spreading the same narrative, some of which included an image similar to the one shared by the suspended account.
On Facebook, we identified two posts with similar language to the screenshot in the initial tweet, one with eight shares and the other with 32 shares. The Facebook posts were found in Groups for neighborhoods or smaller geographic areas and warned others about the need to change their voting.
A Facebook post shared a misleading message above a link to an accurate article from the Orange County Register reporting on Newsom’s executive order.
A post carrying a Facebook fact check label incorrectly states that voters will be turned away at the polls.
The EIP reported this content to Facebook and Twitter as violating both the platforms’ terms of service. Facebook has stated that it will remove content that misrepresents “who can vote, qualifications for voting, whether a vote will be counted and what information and/or materials must be provided in order to vote.” Twitter has stated that it will remove “misleading claims that cause confusion about the established laws, regulations, procedures, and methods of a civic process.” By September 18th, Twitter suspended the initial account, and removed the seven content-related tweets. Facebook removed one of the posts and labeled the other as false information.
The account that posted the initial tweet was part of a pro-Trump follow-for-follow Twitter network. Follow-for-follow communities are an important phenomenon in the spread of misinformation as they create a vehicle for increased engagement. Amplification networks create insulated communities that follow each other and often commit to retweeting each others’ content, and can give the impression of widespread, broader audience engagement when the bulk of it is within the community.
An exemplar tweet from a user who is part This user is part of a left-wing #FBR (#Follow Back Resistance) follow-for-follow amplification network.
This dynamic exists in different political communities. Within right-wing user networks, this phenomenon is known as “Trump Trains”: networks of pro-Trump Twitter accounts that prolifically follow and share each other’s content. A left-wing counterpart dynamic to Trump Trains exists in the #FBR (Follow Back Resistance) follow-for-follow trend, and there are other factional communities that also rely on these dynamics to organize and boost engagement. The EIP will continue monitoring for potential mis or disinformation incidents within Follow for Follow amplification networks across the political spectrum. We are wary that content on these networks may gain a rapid boost in engagement, leading incidents that land in these networks to spread more rapidly than we may otherwise expect.