以量化語料庫方法研究中文“導致”的三個近義詞在不同主題下之語義韻

A study of semantic prosody of three near-synonyms of cause in Mandarin Chinese under different topics: A quantitative corpus-based perspective

巫孟宸(Wu Meng-Chen)

指導教授 ： 陳正賢 ； 萬依萍

國立政治大學/外國語文學院/語言學研究所/碩士(2019年)

https://doi.org/10.6814/THE.NCCU.GIL.001.2019.A07

摘要

本論文之主要目的為探討文本主題如何影響一個詞彙的語義韻 (semantic prosody)。主題在此定義為在新聞類文體中不同類別的文章，其涵蓋文本的範圍小於語域 (register)之範圍。我們查驗了一個混合語義韻之詞 (產生)，與兩個強語義韻之詞 (釀成、促成)在蘋果日報中不同主題下的語義韻分布。我們以規則化的詞語所引列方法來決定這三個詞的語義韻分布，並運用語義網路分析來探尋它們的典型語意場 (semantic field)。研究結果指出，主題對產生的語義韻有中等強烈的影響，但對釀成與促成反而影響程度不大，因此建議了詞彙的語義韻之主題依賴。我們的分析結果指出，新聞文章下的某一主題之內容可能是強化正/負語義韻趨勢的來源，同時揭示了主題下某一詞彙的常規用法。

關鍵字

語義韻 ； 語義偏好 ； 主題 ； 規則化評估 ； 語義網路分析

並列摘要

The objective of this study is to investigate how the semantic prosody (SP) of a lexical item may be mediated by the topic of the texts. Topic is defined as different categories of articles in news genre, covering a smaller scope of texts than register. In particular, we examine the SP distributions of three near synonyms: a mixed-SP node word, i.e., chansheng, and two strong-SP node words, i.e., niangcheng and cucheng, under different topics in the self-collected Apple Daily News corpus. We determine their SP distributions via a rule-based concordance line analysis on the Apple Daily News corpus and utilize semantic network analysis to further discover their prototypical semantic fields. The results indicate that topic has moderately strong effect on chansheng, a mixed-SP node word, but weak effect on niangcheng and cucheng, strong-SP node words, suggesting the topic-dependency of the lexical SP. Our analysis suggests that the subject matters of the news articles under a given topic may be the source that intensifies the positive/negative SP tendency of a node word, and also reveals the conventionalized usage of the node word under the topic.

並列關鍵字

Semantic prosody ； Semantic preference ； Topic ； Rule-based evaluation ； Semantic network analysis

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