- In recent years, there has been a great deal of concern about the proliferation of false and misleading news on social media1,2,3,4. Academics and practitioners alike have asked why people share such misinformation, and sought solutions to reduce the sharing of misinformation5,6,7. Here, we attempt to address both of these questions. First, we find that the veracity of headlines has little effect on sharing intentions, despite having a large effect on judgments of accuracy. This dissociation suggests that sharing does not necessarily indicate belief. Nonetheless, most participants say it is important to share only accurate news. To shed light on this apparent contradiction, we carried out four survey experiments and a field experiment on Twitter; the results show that subtly shifting attention to accuracy increases the quality of news that people subsequently share. Together with additional computational analyses, these findings indicate that people often share misinformation because their attention is focused on factors other than accuracy—and therefore they fail to implement a strongly held preference for accurate sharing. Our results challenge the popular claim that people value partisanship over accuracy8,9, and provide evidence for scalable attention-based interventions that social media platforms could easily implement to counter misinformation online.
- Ranking is still running
- Worked on the workshop paper. Added in a modified version of the intro from the chess paper that uses the GPT-3 now
- Working on literature
- 10:00 Meeting
- 2:00 Meeting
- Turns out that we still have to do a demo. I need to create some data to show what that would look like. Set up a meeting with Vadim for Friday to make sure all the new code is working
- Generated all the scripts – about 700! Tomorrow I’ll run the “sim” and generate training values