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原文連結
論文資訊
- 類型：已發表論文
- 日期：2023-06-08
摘要
Ideological divisions in the United States have become increasingly prominent in daily communication. Accordingly, there has been much research on political polarization, including many recent efforts that take a 計算 perspective. By detecting political biases in a text document, one can attempt to discern and describe its polarity. Intuitively, the named entities (i.e., the nouns and the phrases that act as nouns) and hashtags in text often carry 資訊 about political views. For example, people who use the term "pro-choice" are likely to be liberal and people who use the term "pro-life" are likely to be conservative. In this paper, we seek to reveal political polarities in 社會-media text data and to quantify these polarities by explicitly assigning a polarity score to entities and hashtags. Alt
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