Michael Burnham
Biographic Data
| ID | 3581396 |
|---|---|
| NAME | Michael Burnham |
| GIVEN NAMES | Michael |
| FAMILY NAME | Burnham |
| SIGNATURE | BURNHAM M |
| AFFILIATIONS | Princeton University |
| ORCID | 0000-0002-9946-335X |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 25 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 3 |
Mainstreaming Equitable Climate Action through Growth Management Planning in Washington State, United States
Climate change has already affected the Pacific Northwest in multiple ways, and some jurisdictions across Washington State have begun preparing for climate change by investing in climate adaptation plans or greenhouse gas emission reduction plans. In 2023, Washington State passed House Bill (HB) 1181, a law that expanded the state’s Growth Management Act (RCW 36.70A) to require counties and cities to explicitly address climate risks and vulnerabi…
Political Debate
Social scientists have quickly adopted large language models (LLMs) for their ability to annotate documents without supervised training, an ability known as zero-shot classification. However, due to their computational demands, cost, and often proprietary nature, these models are frequently at odds with open science standards. This article introduces the Political Domain Enhanced BERT-based Algorithm for Textual Entailment (DEBATE) language model…
Stance detection
Stance detection is identifying expressed beliefs in a document. While researchers widely use sentiment analysis for this, recent research demonstrates that sentiment and stance are distinct. This paper advances text analysis methods by precisely defining stance detection and outlining three approaches: supervised classification, natural language inference, and in-context learning. I discuss how document context and trade-offs between resources a…
What is sentiment meant to mean to language models
Sentiment analysis is one of the most widely used text analysis methods in social science. Recent advancements with large language models have made it more accurate and accessible than ever, allowing researchers to classify text with only a plain English prompt. However, “sentiment” entails a wide variety of concepts depending on the domain and tools used. It has been used to mean emotion, opinions, market movements, or simply a general “good-bad…
Perceived risk, political polarization, and the willingness to follow Covid-19 mitigation guidelines
Towards a Definition of Terrorist Ideology
While conventional wisdom holds that the ideology espoused by a terrorist organization is somehow related to that organization’s actions, the precise nature of the relationship between these phenomena is hotly debated, with scholarship often yielding contrasting empirical results. We argue that one reason for this divergence in viewpoints and research findings is an inadequate understanding of what ideology actually is and how it relates to terro…
Perceived risk, political polarization, and the willingness to follow Covid-19 mitigation guidelines
Stance detection
Stance detection is identifying expressed beliefs in a document. While researchers widely use sentiment analysis for this, recent research demonstrates that sentiment and stance are distinct. This paper advances text analysis methods by precisely defining stance detection and outlining three approaches: supervised classification, natural language inference, and in-context learning. I discuss how document context and trade-offs between resources a…
Towards a Definition of Terrorist Ideology
While conventional wisdom holds that the ideology espoused by a terrorist organization is somehow related to that organization’s actions, the precise nature of the relationship between these phenomena is hotly debated, with scholarship often yielding contrasting empirical results. We argue that one reason for this divergence in viewpoints and research findings is an inadequate understanding of what ideology actually is and how it relates to terro…
What is sentiment meant to mean to language models
Sentiment analysis is one of the most widely used text analysis methods in social science. Recent advancements with large language models have made it more accurate and accessible than ever, allowing researchers to classify text with only a plain English prompt. However, “sentiment” entails a wide variety of concepts depending on the domain and tools used. It has been used to mean emotion, opinions, market movements, or simply a general “good-bad…
Towards a Definition of Terrorist Ideology
While conventional wisdom holds that the ideology espoused by a terrorist organization is somehow related to that organization’s actions, the precise nature of the relationship between these phenomena is hotly debated, with scholarship often yielding contrasting empirical results. We argue that one reason for this divergence in viewpoints and research findings is an inadequate understanding of what ideology actually is and how it relates to terro…
Perceived risk, political polarization, and the willingness to follow Covid-19 mitigation guidelines
What is sentiment meant to mean to language models
Sentiment analysis is one of the most widely used text analysis methods in social science. Recent advancements with large language models have made it more accurate and accessible than ever, allowing researchers to classify text with only a plain English prompt. However, “sentiment” entails a wide variety of concepts depending on the domain and tools used. It has been used to mean emotion, opinions, market movements, or simply a general “good-bad…
Mainstreaming Equitable Climate Action through Growth Management Planning in Washington State, United States
Climate change has already affected the Pacific Northwest in multiple ways, and some jurisdictions across Washington State have begun preparing for climate change by investing in climate adaptation plans or greenhouse gas emission reduction plans. In 2023, Washington State passed House Bill (HB) 1181, a law that expanded the state’s Growth Management Act (RCW 36.70A) to require counties and cities to explicitly address climate risks and vulnerabi…
Political Debate
Social scientists have quickly adopted large language models (LLMs) for their ability to annotate documents without supervised training, an ability known as zero-shot classification. However, due to their computational demands, cost, and often proprietary nature, these models are frequently at odds with open science standards. This article introduces the Political Domain Enhanced BERT-based Algorithm for Textual Entailment (DEBATE) language model…
Stance detection
Stance detection is identifying expressed beliefs in a document. While researchers widely use sentiment analysis for this, recent research demonstrates that sentiment and stance are distinct. This paper advances text analysis methods by precisely defining stance detection and outlining three approaches: supervised classification, natural language inference, and in-context learning. I discuss how document context and trade-offs between resources a…
Politics (4 works) · Computer Science (3 works) · Political science (3 works) · Psychology (3 works) · Sentiment Analysis and Opinion Mining (3 works) · Computational and Text Analysis Methods (2 works) · Epistemology (2 works) · Law (2 works) · Misinformation and Its Impacts (2 works) · Philosophy (2 works)