- 學位論文
網路意見評論之中文情感分析
Chinese Sentiment Analysis with Application to Online Opinion Reviews
摘要
本研究提出了一個半監督式情感分析方法，分為兩階段，第一階段採用非監督式情感分析技術，透過SO-PMI計算詞相似度，並生成有主題的情緒詞庫，基於主題情緒詞庫計算情感分數；第二階段分析採用監督式分析中的支持向量機(SVM)做情感分析。本研究提出的新方法可自動找出第一階段的最佳門檻值，以篩選需要進入第二階段分析之資料。 除了根據不同的主題資料生成專屬於此主題的情緒詞庫之外，本研究也考慮了分析錯誤以及人工標記所造成的成本損失。其他分析者在未來做相似運算時，可以根據本研究的損失成本比例來判斷是否適合使用半監督式情感分析方法。
並列摘要
In this paper, we presents a semi-supervised sentiment analysis method, is divided into two stages. The first stage uses the unsupervised sentiment analysis approach that adopts a SO-PMI technique to build the emotion lexicon for different topics. And calculates the emotion score based on the topic emotion lexicon. The second stage analysis uses the supervised sentiment analysis approach that adopts the support vector machine(SVM). The new method proposed in this paper can automatically find the best threshold value of the first stage to select the data that needs to be entered into the second stage analysis. This study also considered the cost loss caused by the analysis error and manual marking. When other analysts do similar operations in the future, it is possible to judge whether the half-supervised affective analysis method is suitable according to the proportion of loss cost in this study.