Riveter: Measuring Power and Social Dynamics Between Entities
conf_acl(2023)
摘要
Riveter provides a complete easy-to-use pipeline for analyzing verb
connotations associated with entities in text corpora. We prepopulate the
package with connotation frames of sentiment, power, and agency, which have
demonstrated usefulness for capturing social phenomena, such as gender bias, in
a broad range of corpora. For decades, lexical frameworks have been
foundational tools in computational social science, digital humanities, and
natural language processing, facilitating multifaceted analysis of text
corpora. But working with verb-centric lexica specifically requires natural
language processing skills, reducing their accessibility to other researchers.
By organizing the language processing pipeline, providing complete lexicon
scores and visualizations for all entities in a corpus, and providing
functionality for users to target specific research questions, Riveter greatly
improves the accessibility of verb lexica and can facilitate a broad range of
future research.
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