6. Discussion
Recent news about the Twitter company is relevant to our research findings. According to an August 23rd, 2022, investigative story in the Given Elon Musk’s purchase of the company in October, 2022 [Our experiments suggest that TME is a remarkably large effect, especially when Twitter itself sends people sensational tweets that have certain visual properties (Experiment 1): tweets with white backgrounds (matching the backgrounds of organic tweets), a brief headline (such as “Breaking News”), and Twitter’s trademark blue checkmark. Experiment 1 yielded a VMP of 87%, with only 2.1% of the participants in the two bias groups expressing any concerns about possible bias in the Twitter feed we showed them. That VMP shift means that in a group of 1,000 undecided voters–split, by definition, 500/500 before exposure to a biased Twitter feed–after viewing that feed, the split will now be 65/935, which means that interacting with the Twitter feed changed a win margin of 0% to a win margin of 87% among vulnerable voters. That shift could occur, in theory, with nearly 98% of the people in such a group having no idea they were manipulated.On its face, a shift that big might seem impossible. In the real world, certainly, people are being influenced by many sources of information, not just by Twitter, and we currently have no reason to believe that Twitter’s content is systematically biased to support just one candidate or political party. But our experiments show the No experiments can show that a source of influence like TME is actually being used. Since 2016, however, our team has been building increasingly larger and more sophisticated systems that capture the ephemeral content being shown to users by Google, YouTube, Bing, Yahoo, and other companies [We acknowledge that if, at some point, we detect political or other bias in Twitter feeds being displayed to certain groups, that will still tell us nothing about the origin of such bias. Bias in ephemeral content can be programmed deliberately [