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.
SPAML is still recruiting collaborators, with contribution opportunities available through the Words2Many and Subs2Strudel pre-projects. SPAM-L admin team is also working on putting together to documents to facilitate contributors’ submission of documents to their local IRB (if necessary), and PI Erin is working on the drafting and submission of a registered report. If you are interested in becoming a collaborator or want to learn more about 007 please email firstname.lastname@example.org
- Corresponding Author
- Project Manager
- Data and Methods
- Kim Peters (Email)
For questions to the whole team: email@example.com.