A Corpus-based Study On Semantic Prosody Of High-frequency Verbs In Agriculture English

The specialized corpus is the reasonable combination of English for specific purposes(ESP, for short) and the corpus linguistics. Recently, the construction and the research on thespecialized corpus has become one of the research hotspots in corpus linguistics. With thedevelopment of the international exchanges and cooperation in agriculture, the teaching andresearching of agricultural English become more and more urgent, especially, for the teachersand the students of agricultural university. The previous agriculture English researches arealmost limited in the teaching reform researches and some lexical features researches forpractical translation, while there are few of researches based on the corpus from the micro-perspective. Semantic prosody is a new research perspective of the corpus linguistic research.It is a language phenomenon which a class of words with the similar semantic features gets ahigh frequency co-occurrence with the key words in the text, which makes the key words itemalso infected similar semantic features, thereby the whole context atmosphere is also filledwith some kind of semantic feature. This language phenomenon was named by Sinclair(1991), then, over the next20or30years, more and more scholars attempt to prove the valueof this language phenomenon in discourse analysis and the application of foreign languageteaching and researching. The study fill the blank on the construction of the agriculturalEnglish Corpus and also fill the gap in agricultural English research from the perspective ofthe semantic prosody, which is worth to explore an learning and teaching approach tostandardize the use of agricultural English.The researcher attempts to answer the following questions:1) What are the high-frequency verbs of the VOA agricultural news reports?2) Is there semantic prosody in agricultural English report? What are the prosodyfeatures of those high-frequency verbs? In other words, do those verbs have a specificsemantic behavior?In order to solve the questions, this study adopts the combination of data-based anddata-driven research approach to explore the semantic prosody. At first, we construct the VOA(Voice of America, or VOA) agricultural English news report corpus. This corpus collected592VOA agriculture English news report texts from2002to2013, with the total size of about220000running words. Through searching and analyzing the collocation and the colligationof the high-frequency verbs by PowerConc, we can explore the semantic prosody features of agricultural English high-frequency verbs, which help understand better the VOA agricultureEnglish texts and the use of the high-frequency verbs.Major findings are:(1) in the top30verbs of the VOA verb list, about half of them, aregeneral words, such as,“say, make, use”；the other half part are the verbs with the agriculturalfeatures, such as “produce, eat, grow”;(2)semantic prosody of agricultural English verbs havetheir unique features: a)most agricultural high-frequency verbs, such as“produce, provide,protect”, convey the positive semantic prosody in these texts; b)“produce” presentsoutstanding positive features with the high frequency colligation:"V+Adj+N"; c) while,“cause” conveys a strong negative semantic prosody, which is not restricted by the colligation;d)“spread” in the VOA texts has obvious negative semantic prosody, and its collocates arealways some things related to the diseases and bacteria. In this thesis, we will analyze thesemantic prosodies of “produce, cause, spread” in detail. Since a contrast of semantic prosodyin agricultural English and general English has not been explored before, this study willdefinitely fill this gap. To a certain extent, this study from the microscopic perspective ofsemantic prosody in agriculture English, will promote the development of agriculture Englishteaching and researching, and provide an instructive reference for the construction of theagricultural English corpus and the corpus-based agricultural English researches in the future.