Research Article
The Influence of Word Attribute Information and Word Frequency Information on the Concreteness Effect of Words
@INPROCEEDINGS{10.1007/978-3-030-62483-5_31, author={Sun Fang and Sui Xue}, title={The Influence of Word Attribute Information and Word Frequency Information on the Concreteness Effect of Words}, proceedings={Green Energy and Networking. 7th EAI International Conference, GreeNets 2020, Harbin, China, June 27-28, 2020, Proceedings}, proceedings_a={GREENETS}, year={2020}, month={11}, keywords={Concreteness effect Word attributes Word frequency Chinese two-character word}, doi={10.1007/978-3-030-62483-5_31} }- Sun Fang
Sui Xue
Year: 2020
The Influence of Word Attribute Information and Word Frequency Information on the Concreteness Effect of Words
GREENETS
Springer
DOI: 10.1007/978-3-030-62483-5_31
Abstract
Using ERP recording technology our purpose is to explore the neural mechanism of the effect of word attribute information and word frequency information on concreteness. Experiment 1: under the lexical judgment task, the relationship between the two variables was investigated. The results showed that in N2 and P3 time window, there were differences between noun and verb processing. In P3 time window, concrete words and abstract words appear separate. In the process of N400, there are differences in the processing of nouns and verbs, concrete words and abstract words. In experiment 2, under the vocabulary judgment task, frequency and vocabulary type were taken as independent variables. The results showed that in N2 time window, high frequency vocabulary and low frequency vocabulary processing were separated. In P3 time window, noun and verb processing differences, concrete and abstract words began to appear separate. In N400, there are differences in the processing of nouns and verbs, concrete words and abstract words. The results suggest that word attributes and word types affect concreteness effect; the concreteness effect occurs in low-frequency words. The processing of concreteness effect of Chinese two-character words supports a single semantic processing model.
