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Title:
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Patterns of Stance in English
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Author:
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Kristen Precht
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Email:
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click here to access email
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Homepage:
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www.kprecht.net
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Degree Awarded:
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Northeastern IIllinois University
, Applied Linguistics
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Degree Date:
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2000
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Linguistic Subfield(s):
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Sociolinguistics
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Subject Language(s):
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English
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Director(s):
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William Grabe
Douglas Biber
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Abstract:
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The study of stance examines the expression of emotion, attitude, certainty and doubt in language. Although there have been many studies on stance in recent years, there is no comprehensive study of individual stance markers across a large, multi-register corpus. This study uses a multi-dimensional approach to identify 1) identifying the main patterns of stance use in English, and 2) interpreting these stance patterns. The corpus for the study is the Longman Corpus of Spoken and Written English, which is comprised of 31 million words in conversation, meetings, news and academic writing in British and American English. The multi-dimensional approach combines computational, quantitative and qualitative analysis techniques. The computational analysis identifying the most common markers of stance and assessing the frequencies of these markers in the corpus. The computer program was designed to assess not only occurrences of lexical items, but also to identify grammatical frames and person marking.
Factor analysis, a multivariate statistical technique, was used to identify co-occurrence patterns of stance markers. Ten unique co-occurrence patterns (factors) are identified. The factors were interpreted on the basis of parts of speech, person marking, semantic properties, register, and discourse function.
Nine of the ten factors could be characterized as either affective or epistemic. Eight of the ten factors seem strongly related to register. Spoken registers are dominant in five factors, and differences in stance mood seem related to discourse context. Written language is dominant in three factors, with fiction, hard science and soft science represented in different factors. Strong patterns were also identified in dialect differences: American and British conversation were identified in separate factors, and showed important differences in function and stance marking.
This study concludes that stance moods are expressed through the systematic use of sets of stance markers. These moods can be identified through a multi-dimensional analysis. Stance is related to register and dialect; person marking and part of speech are also important components of stance expression. The results suggest that multi-dimensional analysis of stance is effective, and that further study of individual registers and dialects would be fruitful. Application to other functional areas is suggested.
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