# Riveter: Measuring Power and Social Dynamics Between Entities

arXiv: https://arxiv.org/abs/2312.09536 · HTML: https://mlsanity.com/paper/2312.09536/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 43 references that are in the map.
- First posted on arXiv 15 Dec 2023.

## Builds on (most cited first, 9 of 9)

- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [PowerTransformer: Unsupervised Controllable Revision for Biased Language Correction](https://mlsanity.com/paper/2010.13816/) (2020)
- [Roles for Computing in Social Change](https://mlsanity.com/paper/1912.04883/) (2019)
- [A Framework for the Computational Linguistic Analysis of Dehumanization](https://mlsanity.com/paper/2003.03014/) (2020)
- [Looking for a Handsome Carpenter! Debiasing GPT-3 Job Advertisements](https://mlsanity.com/paper/2205.11374/) (2022)
- [Multilingual Contextual Affective Analysis of LGBT People Portrayals in Wikipedia](https://mlsanity.com/paper/2010.10820/) (2020)
- [Unpacking Invisible Work Practices, Constraints, and Latent Power Relationships in Child Welfare through Casenote Analysis](https://mlsanity.com/paper/2203.05169/) (2022)
- [Contextual Affective Analysis: A Case Study of People Portrayals in Online #MeToo Stories](https://mlsanity.com/paper/1904.04164/) (2019)
- [Author as Character and Narrator: Deconstructing Personal Narratives from the r/AmITheAsshole Reddit Community](https://mlsanity.com/paper/2301.08104/) (2023)

## Built on by (most cited first, 2 of 2)

- [Hatred Stems from Ignorance! Distillation of the Persuasion Modes in Countering Conversational Hate Speech](https://mlsanity.com/paper/2403.15449/) (2024)
- [A Multilingual Similarity Dataset for News Article Frame](https://mlsanity.com/paper/2405.13272/) (2024)

## Abstract (arXiv)

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.