Concreteness/abstractness ratings for two-character Chinese words in MELD-SCH

Abstract

The concreteness-abstractness continuum is considered a primary dimension in the representation of semantic networks. Its theoretical importance and clinical significance are widely acknowledged. To assist and enhance future research, this study collected and evaluated concreteness/abstractness ratings for 9,877 two-character Chinese words retrieved from the MEga study of Lexical Decision in Simplified CHinese (MELD-SCH, Tsang et al, 2018). The ratings were validated through comparisons with previous rating studies on concreteness and imageability of smaller word samples. Relations of word concreteness with word frequency, age-of-acquisition, and efficiency of lexical processing were also examined. These ratings provide an additional dimension of information to two-character words in the database MELD-SCH, permitting not only more comprehensive research on the Chinese language, but also cross-language investigation of the concreteness effect between Chinese and other languages such as English and Dutch where a large database of concreteness ratings is also available.

Can Masked Emotion-Laden Words Prime Emotion-Label Words? An ERP Test on the Mediated Account

“…The third limitation is that we did not control the concreteness between emotion-label words and emotion-laden words. We retrieved the concreteness of primes and targets from a recent Chinese normative database (Xu and Li, 2020 ) and found that emotion-label words (48 words were found) were more abstract than emotion-laden words (60 words were found), [ F (1, 106) = 61.426, p < 0.001]. Therefore, the distinction between the two kinds of words can be attributed to the influence of concreteness.…”

An ERP megastudy of Chinese word recognition

“…Only the number of homophones were included in LME modeling because the number of pronunciations have a rather restricted range (most characters only have 1 or 2 pronunciations). For semantic variable, concreteness ratings recently became available for over 9800 two‐character words in simplified Chinese (5‐point Likert scale, 1 = very concrete, and 5 = very abstract; Xu & Li, 2020). Considering that concreteness is a semantic variable and should be independent of the simplified versus traditional scripts, it was taken as a word level semantic variable (available for 469 items out of the 1020 chosen words) in this study, along with the character level semantic transparency.…”

“…The main set of models included 1017 items (three items discarded from the full set of 1020 because they have less than 30 valid data points), with the fixed effects (1) the three dummy-coded region variables (2) word number of strokes, (3) log-transformed word contextual diversity, 3 (4) log-transformed 1st character and 2nd character contextual diversity, (5) log-transformed 1st character and 2nd character number of homophones, and (6) 1st character and 2nd character semantic transparency ratings. The second, supplementary set of models included a subset of 469 items that have concreteness ratings (Xu & Li, 2020). The fixed effects of this set included all variables in the main set plus word concreteness ratings.…”

Similarities and differences in the neural representations of abstract concepts across English and Mandarin

“…Although the category labels were never mentioned nor presented to participants, they are listed here in parentheses for expository purposes, preceding Concept abstractness ratings were compared across the languages. English abstractness ratings were obtained from the Brysbaert, Warriner, and Kuperman (2014) database while Mandarin ratings were obtained from MELD-SCH (Xu & Li, 2020). Because the concepts in the MELD-SCH were limited to words with two characters, abstractness comparisons were restricted to the 18 concepts present in both databases (18 of 28 concepts), r(16) = .64, p < .01.…”