16 citations · 72 across the 22 of their papers we have counts for
23 papers · 1 filter
It's How You Ask: Gender-Associated Linguistic Bias in LLMs
Katherine Van Koevering, Anjalie Field
Professional communication is increasingly mediated by LLMs - but do these models serve all users equally? We show that when prompts contain linguistic features more commonly used…
Unrequited Emotions: Investigating the Gaps in Motivation and Practice in Speech Emotion Recognition Research
Taryn Wong, Zeerak Talat, Hanan Aldarmaki +1
Critical analyses of emotion recognition technology have raised ethical concerns around task validity and potential downstream impacts, urging researchers to ensure alignment betwe…
How do we measure privacy in text? A survey of text anonymization metrics
Yaxuan Ren, Krithika Ramesh, Yaxing Yao +1
In this work, we aim to clarify and reconcile metrics for evaluating privacy protection in text through a systematic survey. Although text anonymization is essential for enabling N…
Does Local News Stay Local?: Online Content Shifts in Sinclair-Acquired Stations
Miriam Wanner, Sophia Hager, Anjalie Field
Local news stations are often considered to be reliable sources of non-politicized information, particularly local concerns that residents care about. Because these stations are tr…
Controlled Generation for Private Synthetic Text
Zihao Zhao, Anjalie Field
Text anonymization is essential for responsibly developing and deploying AI in high-stakes domains such as healthcare, social services, and law. In this work, we propose a novel me…
SynthTextEval: Synthetic Text Data Generation and Evaluation for High-Stakes Domains
Krithika Ramesh, Daniel Smolyak, Zihao Zhao +4
We present SynthTextEval, a toolkit for conducting comprehensive evaluations of synthetic text. The fluency of large language model (LLM) outputs has made synthetic text potentiall…
Evaluating Differentially Private Synthetic Data Generation in High-Stakes Domains
Krithika Ramesh, Nupoor Gandhi, Pulkit Madaan +3
The difficulty of anonymizing text data hinders the development and deployment of NLP in high-stakes domains that involve private data, such as healthcare and social services. Poor…
Locating Information Gaps and Narrative Inconsistencies Across Languages: A Case Study of LGBT People Portrayals on Wikipedia
Farhan Samir, Chan Young Park, Anjalie Field +2
To explain social phenomena and identify systematic biases, much research in computational social science focuses on comparative text analyses. These studies often rely on coarse c…
Riveter: Measuring Power and Social Dynamics Between Entities
Maria Antoniak, Anjalie Field, Jimin Mun +3
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 sen…
Developing Speech Processing Pipelines for Police Accountability
Anjalie Field, Prateek Verma, Nay San +2
Police body-worn cameras have the potential to improve accountability and transparency in policing. Yet in practice, they result in millions of hours of footage that is never revie…
Examining risks of racial biases in NLP tools for child protective services
Anjalie Field, Amanda Coston, Nupoor Gandhi +4
Although much literature has established the presence of demographic bias in natural language processing (NLP) models, most work relies on curated bias metrics that may not be refl…
Gendered Mental Health Stigma in Masked Language Models
Inna Wanyin Lin, Lucille Njoo, Anjalie Field +4
Mental health stigma prevents many individuals from receiving the appropriate care, and social psychology studies have shown that mental health tends to be overlooked in men. In th…
Mention Annotations Alone Enable Efficient Domain Adaptation for Coreference Resolution
Nupoor Gandhi, Anjalie Field, Emma Strubell
Although recent neural models for coreference resolution have led to substantial improvements on benchmark datasets, transferring these models to new target domains containing out-…
Challenges and Opportunities in Information Manipulation Detection: An Examination of Wartime Russian Media
Chan Young Park, Julia Mendelsohn, Anjalie Field +1
NLP research on public opinion manipulation campaigns has primarily focused on detecting overt strategies such as fake news and disinformation. However, information manipulation in…
A Survey of Race, Racism, and Anti-Racism in NLP
Anjalie Field, Su Lin Blodgett, Zeerak Waseem +1
Despite inextricable ties between race and language, little work has considered race in NLP research and development. In this work, we survey 79 papers from the ACL anthology that…
Controlled Analyses of Social Biases in Wikipedia Bios
Anjalie Field, Chan Young Park, Kevin Z. Lin +1
Social biases on Wikipedia, a widely-read global platform, could greatly influence public opinion. While prior research has examined man/woman gender bias in biography articles, po…
Multilingual Contextual Affective Analysis of LGBT People Portrayals in Wikipedia
Chan Young Park, Xinru Yan, Anjalie Field +1
Specific lexical choices in narrative text reflect both the writer's attitudes towards people in the narrative and influence the audience's reactions. Prior work has examined descr…
Demoting Racial Bias in Hate Speech Detection
Mengzhou Xia, Anjalie Field, Yulia Tsvetkov
In current hate speech datasets, there exists a high correlation between annotators' perceptions of toxicity and signals of African American English (AAE). This bias in annotated t…
A Generative Approach to Titling and Clustering Wikipedia Sections
Anjalie Field, Sascha Rothe, Simon Baumgartner +2
We evaluate the performance of transformer encoders with various decoders for information organization through a new task: generation of section headings for Wikipedia articles. Ou…
Unsupervised Discovery of Implicit Gender Bias
Anjalie Field, Yulia Tsvetkov
Despite their prevalence in society, social biases are difficult to identify, primarily because human judgements in this domain can be unreliable. We take an unsupervised approach…
Entity-Centric Contextual Affective Analysis
Anjalie Field, Yulia Tsvetkov
While contextualized word representations have improved state-of-the-art benchmarks in many NLP tasks, their potential usefulness for social-oriented tasks remains largely unexplor…
Framing and Agenda-setting in Russian News: a Computational Analysis of Intricate Political Strategies
Anjalie Field, Doron Kliger, Shuly Wintner +3
Amidst growing concern over media manipulation, NLP attention has focused on overt strategies like censorship and "fake news'". Here, we draw on two concepts from the political sci…
Authorship Analysis of Xenophon's Cyropaedia
Anjalie Field
In the past several decades, many authorship attribution studies have used computational methods to determine the authors of disputed texts. Disputed authorship is a common problem…