An Examination of the Disparities Between Traditional and Simplified Chinese Using Complex Network Analysis of Word Co-Occurrence Networks

Abstract

At the moment, the majority of research comparing simplified and traditional Chinese exclusively
looks at character or lexical distinctions, ignoring general disparities. This study suggests using complex network
analysis of word co-occurrence networks, which have been effectively used in language analysis research and
can address global characters and investigate the distinctions between simplified and traditional Chinese, to
address this issue. Specifically, we used a few chosen news corpora to build a word co-occurrence network for
both simplified and traditional Chinese. To obtain a comprehensive knowledge of these networks, advanced
network analysis techniques were then carried out, such as motif analysis, kernel lexicon comparison, and
network statistics analysis. Following that, the networks were contrasted using the acquired attributes. Three
intriguing outcomes can be obtained by comparison: First, simplified Chinese and traditional Chinese cooccurrence networks are scale-free and small-world networks. Third, motif analysis reveals no difference
between the simplified Chinese network and the corresponding traditional Chinese network, indicating semantic
consistency between simplified and traditional Chinese. Nevertheless, given the same corpus size, the cooccurrence networks of traditional Chinese tend to have more nodes, which may be due to a large number of
one-to-many character/word mappings from simplified Chinese to traditional Chinese; second, the traditional
Chinese kernel lexicons have more entries than the simplified Chinese kernel lexicons because traditional
Chinese retains more ancient Chinese words and uses fewer weak verbs.