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| Title: | 應用情感分析在台灣立法院委員會會議發言
Application of Sentiment Analysis in the Committee Speeches of Taiwan Legislative Yuan Members |
| Authors: | 蔡佳穎
Tsai, Chia-Ying |
| Contributors: | 蔡炎龍
邱訪義
Tsai, Yen-Lung
Chiou, Fang-Yi
蔡佳穎
Tsai, Chia-Ying |
| Keywords: | 自然語言處理
BERT
情感分析
部門聲譽
議會發言
NLP
BERT
Sentiment Analysis
Agency Reputation
Parliamentary Speeches |
| Date: | 2024 |
| Issue Date: | 2024-03-01 13:59:38 (UTC+8) |
| Abstract: | Transformer的架構在自然語言處理領域中具有重要的貢獻，其自注意機制和多頭注意力機制的設計使模型能夠更好地捕捉句子中的語義資訊。例如，BERT和GPT等模型均採用了Transformer的架構。在本文中，我們採用了 BERT模型，針對台灣立法委員在委員會會議中對各個部門的質詢發言進行情感分析。透過對這些發言的分類，我們統整了不同情感的數量後，再去計算負面情感的比率，以深入分析不同部門在四年期間聲譽的變化情況。
The Transformer architecture has made significant contributions to the field of natural language processing, allowing models to more effectively capture semantic information within sentences through its self-attention and multi-head attention mechanisms, such as BERT and GPT. In this study, we utilized the BERT model to perform sentiment analysis on parliamentary speeches by Taiwanese legislators during committee meetings. Our specific focus was on interpellations directed at various government agencies. By categorizing these speeches, we aggregated the quantities of different sentiments to calculate the negative ratio, offering an in-depth analysis of the changing reputation of different agencies over a four-year period. |
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| Description: | 碩士
國立政治大學
應用數學系
110751002 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0110751002 |
| Data Type: | thesis |
| Appears in Collections: | [應用數學系] 學位論文
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