Zobrazeno 1 - 10
of 527
pro vyhledávání: '"TUCKER, JOSHUA"'
Existing text scaling methods often require a large corpus, struggle with short texts, or require labeled data. We develop a text scaling method that leverages the pattern recognition capabilities of generative large language models (LLMs). Specifica
Externí odkaz:
http://arxiv.org/abs/2310.12049
Existing approaches to estimating politicians' latent positions along specific dimensions often fail when relevant data is limited. We leverage the embedded knowledge in generative large language models (LLMs) to address this challenge and measure la
Externí odkaz:
http://arxiv.org/abs/2303.12057
Text analysis in the social sciences often involves using specialized dictionaries to reason with abstract concepts, such as perceptions about the economy or abuse on social media. These dictionaries allow researchers to impart domain knowledge and n
Externí odkaz:
http://arxiv.org/abs/2210.15172
To mitigate the spread of fake news, researchers need to understand who visit fake new sites, what brings people to those sites, where visitors come from, and what content they prefer to consume. In this paper, we analyze web traffic data from The Ga
Externí odkaz:
http://arxiv.org/abs/2201.04226
Autor:
Tucker, Joshua.
Publikováno v:
Connect to the thesis.
Thesis (B.A.)--Haverford College, Dept. of English, 2004.
Includes bibliographical references.
Includes bibliographical references.
Externí odkaz:
http://thesis.haverford.edu/89/01/2004TuckerJ.pdf
