Experiment 1: Pre- and post-manipulation mean voting preferences on 11-point scale (corrected so that positive values indicate preference for the favored candidate).
ARRESTED
In the bias groups, only seven participants (out of 336, 2.1%) expressed concerns about possible bias in the content of the tweets; whereas 113 of these individuals (33.6%) commented specifically on the damaging (but never the positive) information in the biased TMs. Comments such as, “Read that Bill Shorten spent tax payer money, arrested for DUI and had an affair” and “Scott Morrison displayed a lot of bad judgment in his personal life (affairs, DUI arrests, etc.), which made me feel he was untrustworthy,” were common. People’s focus on the negative content in the TMs is addressed in Experiment 4 below, as well as in our Discussion section.As we noted, Twitter’s TMs look almost exactly like the organic tweets of Twitter users. The main feature that consistently distinguishes the company’s TMs from most organic tweets is that their TMs all include the prestigious blue checkmark. In Experiment 2, we attempted to replicate our findings from Experiment 1 while omitting the blue checkmarks from our TMs.