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4.1 Frequency Distribution of the Synonyms ....... 23 
4.2 Error Analysis ....... 27 
4.2.1 Error Analysis in Terms of Word Colligation ....... 27 
4.2.2 Error Analysis in Terms of Word Collocation....... 32 
4.2.3 Error Analysis in Terms of Semantic Prosody ...... 35 
4.3 Discussion ....... 40 
Chapter Five Conclusion ......... 42 
5.1 Major Findings ..... 42 
5.2 Pedagogical Implications ........ 43 
5.3 Limitations and Suggestions for Future Research ...... 44 

Chapter Four Error Analysis and Discussion 

In this chapter, frequency distributions of the synonyms end，stop，close，finish and  conclude  are  described  respectively  and  errors  made  by  Chinese  learners  of English are analyzed from the perspectives of colligation, collocation and semantic prosody. The underlying reasons causing these errors will also be discussed. 

4.1 Frequency Distribution of the Synonyms

Synonyms  can  be  discriminated  based  on  corpus  in  terms  of  register, colligation, collocation and semantic prosody. However, in CLEC, the linguistic data are  sampled  from  compositions,  so  this  study  will  not  focus  on  the  distribution  of each  word  in  different  registers  but  word  frequency  in  each  corpus.  In  this  section, features of the synonyms in terms of word frequency are presented in order to find out  the  differences  between  Chinese  learners  of  English  and  native  speakers  of English in the use of the synonyms of end.  Word  frequency  analysis  is  essential  and  fundamental  in  corpus-based  studies as  it  shows  clearly  the  various  frequencies  of  each  word  occurring  in  the  same corpus  or  different  corpora.  This  part  will  examine  the  synonyms  of  end  collected from  the  two  corpora  and  analyze  their  distributions,  with  the  aim  to  see  whether there  are  significant  differences  in  frequency  distribution  between  Chinese  learners of English and native speakers of English. As  the  verb  forms  of  these  synonyms  are  to  be  studied,  tagging  the part-of-speech  (POS)  of  the  linguistic  data  becomes  a  necessity.  COCA  provides linguistic  data  annotated  by  the  commercial  POS  tagger  software  CLAWS  7,  so  the first step is to tag the concordance lines of them one by one in CLEC by using the free  software  Tree Tagger  and  clear  them  manually.  The  accuracy  rates  of  CLAWS and Tree Tagger are both about 96%-97%.  

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