A Corpus-Based Study On Derivational Affixes In English For Science And Technology

The present study aims at analyzing the distribution characteristics of derivational affixes in English for Science and Technology (EST) by comparing the derivational affixes occurring in JDEST with those occurring in BNC. Visual Foxpro and SPSS were used to obtain relevant data, and both qualitative and quantitative analyses were made.The study shows that compared with general English, EST employs more prefix types, and the total number of prefix tokens is significantly larger; moreover, the number of word types formed by prefixes is significantly larger. In EST, the distribution of different semantic categories of prefixes in word forming has its own characteristics. The prefixes in the semantic category Negative and Time & Space produce more than half of the word types formed by the prefixes in EST. The prefixes in the semantic category Degree, Number and Other are favored more in EST than in general English. The prefixes of Greek origin produce significantly more word types in EST than in general English. The number of suffix types employed in EST has no significant difference from that in general English. Although the number of suffix tokens in EST is larger than that in general English, the number of word types formed with suffixes is relatively smaller in EST. In EST, among the four grammatical categories of suffixes, the noun suffixes produce the most word types, and they play a more important role in word forming than in general English. The Latin suffixes and Greek suffixes play a more important role in word forming in EST, compared with general English.