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The Effect of Neighborhood Size and Morphology in the Chinese LanguageNguyen, Long 01 January 2016 (has links)
The Neighborhood Size Effect (NSE), characterized as the effect in word determination based on changing one orthographic aspect of that word. The amount of words that can be created through such manipulation is called a neighborhood size (NS). Number of other factors such as frequency, how often a word appears and morphology, the combination of meaningful word units, have been suggested to have an overriding effect on NSE. In addition, there is a lack of research on NSE with non-alphabetical languages such as Chinese, which uses characters comprising of a multitude of semantic or phonetic markers. In this experiment, participants coming from mainland China were presented with 60 individual characters and 59 characters with Chinese morphology made up of two characters which form single words. Both conditions, were manipulated with NS by adjusting the semantic or phonetical radical within a character and with frequency by using a website that measures how frequent a character appeared within the language. Both character conditions were found to have a significant effect with frequency and neighborhood size (NS) with characters with higher frequency and lower NS found to have higher accuracy and lower reaction times. With low frequency single characters, it was that those with higher neighborhood size had greater delay in reaction time and lower accuracy. With low frequency morphologically constructed characters, it was found that lower neighborhood size had higher accuracy, but no significant result with regards to reaction time. Due to differing accuracy results with NS and character condition, it is suggested that further factors such as morphological processing in single characters and bigram frequency in morphologically constructed characters might have an effect on word determination in conjunction with neighborhood size. Thus, it is a possibility that Chinese morphological may depend more on other factors than neighborhood size.
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