Affective and psycholinguistic norms of Greek words: Manipulating their affective or psycho-linguistic dimensions

Author(s):  
Potheini Vaiouli ◽  
Maria Panteli ◽  
Georgia Panayiotou
2018 ◽  
Vol 71 (5) ◽  
pp. 1057-1069 ◽  
Author(s):  
Patrick Bonin ◽  
Alain Méot ◽  
Jean-Michel Boucheix ◽  
Aurélia Bugaiska

We provide psycholinguistic norms for a new set of 160 French idiomatic expressions and 160 proverbs: knowledge, predictability, literality, compositionality, subjective and objective frequency, familiarity, age of acquisition (AoA) and length. Different analyses (reliability, descriptive statistics and correlations) performed on the norms are reported and discussed. The norms can be downloaded as Supplemental Material .


2015 ◽  
Author(s):  
James Gibson ◽  
Nikolaos Malandrakis ◽  
Francisco Romero ◽  
David C. Atkins ◽  
Shrikanth S. Narayanan

2004 ◽  
Vol 36 (1) ◽  
pp. 127-139 ◽  
Author(s):  
Patrick Bonin ◽  
Bruno Boyer ◽  
Alain Méot ◽  
Michel Fayol ◽  
Sylvie Droit

2007 ◽  
Vol 39 (2) ◽  
pp. 192-198 ◽  
Author(s):  
Youyi Liu ◽  
Hua Shu ◽  
Ping Li

2020 ◽  
Author(s):  
Patrick C. Trettenbrein ◽  
Nina-Kristin Pendzich ◽  
Jens-Michael Cramer ◽  
Markus Steinbach ◽  
Emiliano Zaccarella

Sign language offers a unique perspective on the human faculty of language by illustrating that linguistic abilities are not bound to speech and writing. In studies of spoken and written language processing, lexical variables such as, for example, age of acquisition have been found to play an important role, but such information is not as yet available for German Sign Language (Deutsche Gebärdensprache, DGS). Here, we present a set of norms for frequency, age of acquisition, and iconicity for more than 300 lexical DGS signs, derived from subjective ratings by 32 deaf signers. We also provide additional norms for iconicity and transparency for the same set of signs derived from ratings by 30 hearing non-signers. In addition to empirical norming data, the dataset includes machine-readable information about a sign’s correspondence in German and English, as well as annotations of lexico-semantic and phonological properties: one-handed vs. two-handed, place of articulation, most likely lexical class, animacy, verb type, (potential) homonymy, and potential dialectal variation. Finally, we include information about sign onset and offset for all stimulus clips from automated motion-tracking data. All norms, stimulus clips, data, as well as code used for analysis are made available through the Open Science Framework in the hope that they may prove to be useful to other researchers: https://osf.io/mz8j4/


2020 ◽  
Vol 52 (3) ◽  
pp. 1056-1072 ◽  
Author(s):  
Francesca M. M. Citron ◽  
Mollie Lee ◽  
Nora Michaelis

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