Oscar Stuhler
Biographic Data
| ID | 925484 |
|---|---|
| NAME | Oscar Stuhler |
| GIVEN NAMES | Oscar |
| FAMILY NAME | Stuhler |
| SIGNATURE | STUHLER O |
| AFFILIATIONS | New York University |
| ORCID | 0000-0001-7391-1743 |
| VERIFIED | Yes |
| TOTAL WORKS | 11 |
| TOTAL CITATIONS | 45 |
| WORKS AS AUTHOR | 11 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 4 |
When nature has agency
This paper examines the extent to which traditional worldviews and mental models of the natural world are related to contemporary environmental attitudes, policy preferences, and outcomes. We extract information from a corpus of traditional folktales to study how nature – such as animals, insects, and plants – is portrayed across societies. Specifically, we construct ethnicity-level measures capturing how frequently natural entities appear in a g…
Time and Climate Change
Questions of temporality are at the heart of climate change discourse: Does one think of climate change primarily as an event happening in the present, or as something that will take place in the future? By when must we take action to prevent its worst consequences? This article presents the first large-scale assessment of the structure and evolution of temporalities expressed in U.S. media discussions on climate change (2000 to 2021). To do so, …
The cultural construction of personal relationships
Generative AI in Sociological Research
Generative artificial intelligence (GenAI) has garnered considerable attention for its poten- tial utility in research and scholarship, even among those who typically do not rely on computational tools. However, early commentators have also articulated concerns about how GenAI usage comes with enormous environmental costs, serious social risks, and a tendency to produce low-quality content. In the midst of both excitement and skepticism, it is cr…
Bottom Up? Top Down? Determinants of Issue-Attention in State Politics
Who shapes the issue-attention cycle of state legislators? Although state governments make critical policy decisions, data and methodological constraints have limited researchers’ ability to study state-level agenda setting. For this article, we collect more than 122 million Twitter messages sent by state and national actors in 2018 and 2021. We then employ supervised machine learning and time series techniques to study how the issue attention of…
From Codebooks to Promptbooks
Generative AI (GenAI) is quickly becoming a valuable tool for sociological research. Already, sociologists employ GenAI for tasks like classifying text and simulating human agents. We point to another major use case: the extraction of structured information from unstructured text. Information Extraction (IE) is an established branch of Natural Language Processing, but leveraging the affordances of this paradigm has thus far required familiarity w…
Politics as Usual? Measuring Populism, Nationalism, and Authoritarianism in U.S. Presidential Campaigns (1952–2020) with Neural Language Models
Radical-right campaigns commonly employ three discursive elements: anti-elite populism, exclusionary and declinist nationalism, and authoritarianism. Recent scholarship has explored whether these frames have diffused from radical-right to centrist parties in the latter’s effort to compete for the former’s voters. This study instead investigates whether similar frames had been used by mainstream political actors prior to their exploitation by the …
Reclaiming the Past to Transcend the Present
Nostalgic appeals to an idealized past are often employed in radical‐right discourse. In this study, we examine precedents for this strategy in mainstream politics. We make use of recent advances in natural language processing—specifically Transformer‐based neural language models and active learning—to identify instances of nostalgia in U.S. presidential campaign speeches from 1952 to 2020. We then ask what form nostalgia takes, when it has been …
Who Does What to Whom? Making Text Parsers Work for Sociological Inquiry
Over the past decade, sociologists have become increasingly interested in the formal study of semantic relations within text. Most contemporary studies focus either on mapping concept co-occurrences or on measuring semantic associations via word embeddings. Although conducive to many research goals, these approaches share an important limitation: they abstract away what one can call the event structure of texts, that is, the narrative action that…
What's in a category? A new approach to Discourse Role Analysis
Relating social and symbolic relations in quantitative text analysis. A study of parliamentary discourse in the Weimar Republic
Relating social and symbolic relations in quantitative text analysis. A study of parliamentary discourse in the Weimar Republic
Reclaiming the Past to Transcend the Present
Nostalgic appeals to an idealized past are often employed in radical‐right discourse. In this study, we examine precedents for this strategy in mainstream politics. We make use of recent advances in natural language processing—specifically Transformer‐based neural language models and active learning—to identify instances of nostalgia in U.S. presidential campaign speeches from 1952 to 2020. We then ask what form nostalgia takes, when it has been …
What's in a category? A new approach to Discourse Role Analysis
Who Does What to Whom? Making Text Parsers Work for Sociological Inquiry
Over the past decade, sociologists have become increasingly interested in the formal study of semantic relations within text. Most contemporary studies focus either on mapping concept co-occurrences or on measuring semantic associations via word embeddings. Although conducive to many research goals, these approaches share an important limitation: they abstract away what one can call the event structure of texts, that is, the narrative action that…
From Codebooks to Promptbooks
Generative AI (GenAI) is quickly becoming a valuable tool for sociological research. Already, sociologists employ GenAI for tasks like classifying text and simulating human agents. We point to another major use case: the extraction of structured information from unstructured text. Information Extraction (IE) is an established branch of Natural Language Processing, but leveraging the affordances of this paradigm has thus far required familiarity w…
Bottom Up? Top Down? Determinants of Issue-Attention in State Politics
Who shapes the issue-attention cycle of state legislators? Although state governments make critical policy decisions, data and methodological constraints have limited researchers’ ability to study state-level agenda setting. For this article, we collect more than 122 million Twitter messages sent by state and national actors in 2018 and 2021. We then employ supervised machine learning and time series techniques to study how the issue attention of…
Relating social and symbolic relations in quantitative text analysis. A study of parliamentary discourse in the Weimar Republic
What's in a category? A new approach to Discourse Role Analysis
Politics as Usual? Measuring Populism, Nationalism, and Authoritarianism in U.S. Presidential Campaigns (1952–2020) with Neural Language Models
Radical-right campaigns commonly employ three discursive elements: anti-elite populism, exclusionary and declinist nationalism, and authoritarianism. Recent scholarship has explored whether these frames have diffused from radical-right to centrist parties in the latter’s effort to compete for the former’s voters. This study instead investigates whether similar frames had been used by mainstream political actors prior to their exploitation by the …
Reclaiming the Past to Transcend the Present
Nostalgic appeals to an idealized past are often employed in radical‐right discourse. In this study, we examine precedents for this strategy in mainstream politics. We make use of recent advances in natural language processing—specifically Transformer‐based neural language models and active learning—to identify instances of nostalgia in U.S. presidential campaign speeches from 1952 to 2020. We then ask what form nostalgia takes, when it has been …
Who Does What to Whom? Making Text Parsers Work for Sociological Inquiry
Over the past decade, sociologists have become increasingly interested in the formal study of semantic relations within text. Most contemporary studies focus either on mapping concept co-occurrences or on measuring semantic associations via word embeddings. Although conducive to many research goals, these approaches share an important limitation: they abstract away what one can call the event structure of texts, that is, the narrative action that…
The cultural construction of personal relationships
Generative AI in Sociological Research
Generative artificial intelligence (GenAI) has garnered considerable attention for its poten- tial utility in research and scholarship, even among those who typically do not rely on computational tools. However, early commentators have also articulated concerns about how GenAI usage comes with enormous environmental costs, serious social risks, and a tendency to produce low-quality content. In the midst of both excitement and skepticism, it is cr…
Bottom Up? Top Down? Determinants of Issue-Attention in State Politics
Who shapes the issue-attention cycle of state legislators? Although state governments make critical policy decisions, data and methodological constraints have limited researchers’ ability to study state-level agenda setting. For this article, we collect more than 122 million Twitter messages sent by state and national actors in 2018 and 2021. We then employ supervised machine learning and time series techniques to study how the issue attention of…
From Codebooks to Promptbooks
Generative AI (GenAI) is quickly becoming a valuable tool for sociological research. Already, sociologists employ GenAI for tasks like classifying text and simulating human agents. We point to another major use case: the extraction of structured information from unstructured text. Information Extraction (IE) is an established branch of Natural Language Processing, but leveraging the affordances of this paradigm has thus far required familiarity w…
When nature has agency
This paper examines the extent to which traditional worldviews and mental models of the natural world are related to contemporary environmental attitudes, policy preferences, and outcomes. We extract information from a corpus of traditional folktales to study how nature – such as animals, insects, and plants – is portrayed across societies. Specifically, we construct ethnicity-level measures capturing how frequently natural entities appear in a g…
Time and Climate Change
Questions of temporality are at the heart of climate change discourse: Does one think of climate change primarily as an event happening in the present, or as something that will take place in the future? By when must we take action to prevent its worst consequences? This article presents the first large-scale assessment of the structure and evolution of temporalities expressed in U.S. media discussions on climate change (2000 to 2021). To do so, …
Computational and Text Analysis Methods (6 works) · Linguistics (6 works) · Law (5 works) · Political science (5 works) · Politics (5 works) · Sociology (5 works) · Computer Science (4 works) · Electoral Systems and Political Participation (3 works) · Philosophy (3 works) · Populism, Right-Wing Movements (3 works)