Dear Colleagues,
Hopefully this is quite a simple question:
I'm going to be running some masked semantic congruence priming studies, and am looking for suitable stimuli. Put simply, semantic congruence studies typically show that a target word (e.g., HAWK) is semantically categorised (e.g., Is this an animal?) faster when preceded by a category-congruent/semantically-related prime word (e.g., eagle) compared to when preceded by a semantically unrelated word (e.g., knee).
The first thing I want to do is to replicate the classic finding using a larger set of stimuli. I will need at least 90 target words, each with a semantically-related prime-word. In line with previous studies (e.g., Quinn & Kinoshita, 2008), a lot of my stimuli will be drawn from McRae et al.'s set of feature norms (which is particularly useful for identifying members of the 'animal' category that have high semantic feature overlap; e.g., cat-dog; sheep-goat; etc.). But to reach 90 targets (each with a semantically similar prime), I will probably need to find a similar, but more dense database.
Ideally, I'm after an easy userface where I can simply input a target word (e.g., hand) that belongs to a category I'm using for the categorisation task (e.g., is this a body-part?) and it provides a list of the most semantically similar words from that category (e.g., if the category is 'body parts' it might output 'head, ankle, shin, foot, etc.). I'm aware there are a few solutions out there - whether it be measures semantic feature overlap or co-occurrence (e.g., wordnet, COALS, LSA, HAL) but I'd favour something with an interface that is easy to use, or even just a large datafile similar to McRae's 2005 set.
Thanks a lot!
Ryan
Quinn, W.M. and Kinoshita, S. (2008) Congruence effect in semantic categorization with masked primes with narrow and broad categories. Journal of Memory and Language, 58, 286–306.
McRae, K., Cree, G. S., Seidenberg, M. S., & McNorgan, C. (2005). Semantic feature production norms for a large set of living and nonliving things. Behavior Research Methods, Instruments, and Computers, 37, 547–559.
Hi Ryan,
if you're looking for an easy to use interface in which you input a word (or multiple words) and it returns the closest N semantic neighbors, then I really recommend using snaut. Additionally, if you already have a list of words, the program can tell you how close they are to one another, or even compare the whole list of primes to the respective targets. I found it very useful, also for finding the semantic neighbors I missed when coming up with a list of stimuli.
Here's the link to the website with the interface and all the resources: http://meshugga.ugent.be/snaut-english/
Hope it helps!
PS: I have to thank researcher Giorgio Arcara for suggesting snaut to me in the first place, check him out for some some cool studies on language processing!
Hi Tiziano,
Wow, that is exactly what I was looking for - thank you! I will look into Girogio's work too.
Many thanks!
Ryan
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