Semantic priming has been studied for nearly fifty years across various experimental manipulations and theoretical frameworks. Critically, the understanding of semantic priming relies on reliable, well-studied stimuli with defined similarity values. In the last twenty years, the publication rates of normed stimuli databases and corpora (i.e., large bodies of text) has exponentially increased. Further, newer computational models of concept representation have been detailed using these databases. Using these newer models, we can define similarity between concepts to create reliable stimuli for study in semantic priming. In this proposal, we outline the need for a database of semantic priming values, particularly in non-English languages. We detail the process for creating a large database of priming values, from which new theories and hypotheses can be examined. Further, we describe the novel outputs that this proposal will support including a framework for determining sample size for studies of this nature.
This project is in the beginning stages. To learn more about the project check out the proposal or the conference video. The team is working on revise-and-resubmit from Nature Human Behavior. The admin team is additionally working on coding the experiment in lab.js, piloting the experiment, and setting up the system for material translations. The project team will be sending out updates in the near future regarding ways to contribute to the current project. If you are interested in becoming a collaborator, or want to learn more about 007 please email the lead team.
- Corresponding Author
- Project Manager
- Data and Methods
- Kim Peters (Email)
For questions to the whole team: email@example.com.