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Guenther-2022-30 #1509

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5bd0c66
adding dataset
MiraAhmedovic Feb 4, 2026
963bacb
updates version of Hwang-2021-60 merged
MiraAhmedovic Feb 4, 2026
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1 change: 1 addition & 0 deletions concepticondata/conceptlists.tsv
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Expand Up @@ -472,3 +472,4 @@ Soederholm-2013-420 Söderholm, Carina and Häyry, Emilia and Laine, Matti and K
Amsel-2012-559 Amsel, Ben D. and Urbach, Thomas P. and Kutas, Marta 2012 559 ratings English English https://doi.org/10.3758/s13428-012-0215-z Amsel2012 This list of 559 object concepts was rated for perceptual modalities (color, motion, auditory, olfactory, gustatory, graspability, pain) as well as familiarity. Ratings were given on an 8-point scale. 1028-1041
Eilola-2010-210 Eilola, Tiina M. and Havelka, Jelena 2010 210 ratings English, Finnish English, Finnish https://doi.org/10.3758/BRM.42.1.134 Eilola2010 This list of 210 words contains ratings of familiarity, valence, emotionality, offensiveness, and concreteness for Finnish and British English nouns, including 34 taboo words. Ratings were provided by native speakers of each language. For British English in particular, the aim of the study was to collect data comparable to the American English norms in the Affective Norms for English Words database [(Bradley & Lang, 1999)](:bib:Bradley1999). The present mappings were based on the English words. 134-140
Pache-2023-207 Pache, Matthias 2023 207 basic English Chibchan https://doi.org/10.1086/722240 Pache2023 This list was used for a comparative analysis of the Chibchan languages with the aim of revising their internal genealogical classification. The author claims that the list represents the Swadesh 207 list, however, it is unclear which list is meant exactly, since Swadesh never published a list containing 207 words. The list is likely very similar to [Comrie(1977)](:bib:Comrie1977) but uses slightly different glosses. The data for the Chibchan languages was gathered from existing sources on various Chibchan languages. 81-103
Guenther-2022-30 Günther, Fritz and Rinaldi, Luca 2022 30 norms English global https://doi.org/10.1038/s41598-022-12027-5 Guenther2022 This dataset combines cross-linguistic lexical frequency information for body-part terms with anatomical and neurobiological measures of body representation. For each concept, lexical forms are provided for a wide range of languages (Amharic, Arabic, Bengali, Chinese, Croatian, Czech, Dutch, English, German, Greek, Hebrew, Hindi, Hungarian, Italian, Japanese, Latin, Latvian, Malay, Polish, Portuguese, Russian, Somali, Spanish, Swahili, Tagalog, Tamil, Turkish, Urdu, and Yoruba). For each language, separate variables encode the base form, the plural form, overall corpus frequency, and frequency per million words, derived from language-specific corpora. Additionally, the list contains measures of cortical representational size and physical body surface area, which is encoded using anterior–posterior (AP) distinctions. Further, different definitions of "arm" were used: one unit spanning shoulder to wrist (with the hand treated separately), or upper arm (shoulder to elbow) and forearm (elbow to wrist) treated separetely. 1-13
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