자료유형  

 학위논문

Control Number  

0017164418

International Standard Book Number  

9798346387428

Dewey Decimal Classification Number  

006.35

Main Entry-Personal Name  

Burnham, Michael.

Publication, Distribution, etc. (Imprint  

[S.l.] : The Pennsylvania State University., 2024

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2024

Physical Description  

131 p.

General Note  

Source: Dissertations Abstracts International, Volume: 86-05, Section: B.

General Note  

Advisor: Nelson, Michael J.

Dissertation Note  

Thesis (Ph.D.)--The Pennsylvania State University, 2024.

Summary, Etc.  

요약This dissertation explores the how recent advancements in text analysis methods can be applied to political research. In the first chapter, I demonstrate how language models can facilitate opinion mining at a much larger scale than was previously possible, and guide researchers through best practices in employing these methods. In the second chapter, I build on these methods by presenting a method of estimating ideology from text that is based on expressed opinions rather than the choice of words. Finally, in chapter three I demonstrate how these methods enable researchers to ask and answer questions about politics that may have been infeasible previously. The chapter uses text analysis to present the first scaling method for affective polarization among members of congress, and then uses this measure to test how affective polarization influences legislative effectiveness.

Subject Added Entry-Topical Term  

Text categorization.

Subject Added Entry-Topical Term  

Nominations.

Subject Added Entry-Topical Term  

Ideology.

Subject Added Entry-Topical Term  

Sentiment analysis.

Subject Added Entry-Topical Term  

Neural networks.

Subject Added Entry-Topical Term  

Labeling.

Subject Added Entry-Topical Term  

Political parties.

Subject Added Entry-Topical Term  

Political science.

Subject Added Entry-Topical Term  

Attitudes.

Subject Added Entry-Topical Term  

Documents.

Subject Added Entry-Topical Term  

Automatic text analysis.

Subject Added Entry-Topical Term  

Social sciences.

Subject Added Entry-Topical Term  

Semantics.

Subject Added Entry-Topical Term  

Natural language.

Subject Added Entry-Topical Term  

COVID-19.

Subject Added Entry-Topical Term  

Web studies.

Subject Added Entry-Topical Term  

Logic.

Added Entry-Corporate Name  

The Pennsylvania State University.

Host Item Entry  

Dissertations Abstracts International. 86-05B.

Electronic Location and Access  

로그인을 한후 보실 수 있는 자료입니다.

Control Number  

joongbu:657226