Often social scientists want to label whether text is populist or anti-elite in some sense. Traditional methods of content analysis tend to run into one of two problems. Labeling text by hand is taxing, limiting the scope of the analysis. Alternately, labeling text based on political-party affiliation elides variation within political parties and does not tend to work well for two-party systems. I use recent breakthroughs in natural language processing (NLP) combined with supervised learning to explore an alternative way of labeling text as anti-elite that avoids these constraints, allowing sentence-level categorization at scale
This article presents a novel automatic method of text analysis aimed at discovering patterns of lex...
Most automated procedures used for the analysis of textual data do not apply natural language proces...
This dissertation presents content and stylistic solutions for three opinion-oriented text classific...
Often social scientists want to label whether text is populist or anti-elite in some sense. Traditio...
ABSTRACT: The following research discusses text analysis approaches to automatically categorize news...
This work shows the value of word-level statistical data from the US Congressional Record for studyi...
Political conflict unfolds in language. To understand the quest for, and exercise of, power, we must...
This paper investigates the identification of populist rhetoric in text and presents a novel cross-l...
Politics and political conflict often occur in the written and spoken word. Scholars have long recog...
Previous work on extracting ideology from text has focused on domains where expression of political ...
Applications of automated text analysis measuring topics, ideology, sentiment or even personality ar...
Polarizing discussions about political and social issues are common in mass media. Annotations on th...
Polarizing discussions about political and social issues are common in mass media. Annotations on th...
Published online: 15 October 2021One of the main challenges in comparative studies on populism conce...
The purpose of this research project is to delve into political media and gain an insight into how p...
This article presents a novel automatic method of text analysis aimed at discovering patterns of lex...
Most automated procedures used for the analysis of textual data do not apply natural language proces...
This dissertation presents content and stylistic solutions for three opinion-oriented text classific...
Often social scientists want to label whether text is populist or anti-elite in some sense. Traditio...
ABSTRACT: The following research discusses text analysis approaches to automatically categorize news...
This work shows the value of word-level statistical data from the US Congressional Record for studyi...
Political conflict unfolds in language. To understand the quest for, and exercise of, power, we must...
This paper investigates the identification of populist rhetoric in text and presents a novel cross-l...
Politics and political conflict often occur in the written and spoken word. Scholars have long recog...
Previous work on extracting ideology from text has focused on domains where expression of political ...
Applications of automated text analysis measuring topics, ideology, sentiment or even personality ar...
Polarizing discussions about political and social issues are common in mass media. Annotations on th...
Polarizing discussions about political and social issues are common in mass media. Annotations on th...
Published online: 15 October 2021One of the main challenges in comparative studies on populism conce...
The purpose of this research project is to delve into political media and gain an insight into how p...
This article presents a novel automatic method of text analysis aimed at discovering patterns of lex...
Most automated procedures used for the analysis of textual data do not apply natural language proces...
This dissertation presents content and stylistic solutions for three opinion-oriented text classific...