Diyi Yang's guest appearances

Diyi Yang

NLP Highlights

The Interaction Hour

Diaries of Social Data Research

Brendan O'Connor

David Bamman

Stevie Chancellor

Ayanna Howard

Noah Smith

Michael Collins

Charles Isbell

Brandon Stewart

Betsy DiSalvo

Victor Sanh

Ethan Zuckerman

Sam Bowman

Mark Riedl

Nathan Schneider

Matt Gardner

OwlTail

Our guests on this episode are Diyi Yang, assistant professor at the School of Interactive Computing, and David Muchlinski, assistant professor in the Sam Nunn School of International Affairs, both at Georgia Tech. We discuss their EMNLP 2021 paper, "Latent Hatred: A Benchmark for Understanding Implicit Hate Speech." This paper is co-authored with Mai ElSherief, Caleb Ziems, Vaishnavi Anupindi, Jordyn Seybolt, and Munmun De Choudhury. Diyi and David reveal that the annotation process behind this paper took two years and incorporated domain expertise on the broader context around hateful language. That is, an understanding of the social groups who produce this language allowed for better categorization and interpretation of implicit hate. We also discuss the cross-discipline connections they’ve forged in the past and present, and the ongoing challenges this type of work poses for computational methods.

Our guests on this episode are Diyi Yang, assistant professor at the School of Interactive Computing, and David Muchlinski, assistant professor in the Sam Nunn School of International Affairs, both at Georgia Tech. We discuss their EMNLP 2021 paper, "Latent Hatred: A Benchmark for Understanding Implicit Hate Speech." This paper is co-authored with Mai ElSherief, Caleb Ziems, Vaishnavi Anupindi, Jordyn Seybolt, and Munmun De Choudhury. Diyi and David reveal that the annotation process behind this paper took two years and incorporated domain expertise on the broader context around hateful language. That is, an understanding of the social groups who produce this language allowed for better categorization and interpretation of implicit hate. We also discuss the cross-discipline connections they’ve forged in the past and present, and the ongoing challenges this type of work poses for computational methods.

19. Constructing a Taxonomy of Implicit Hate Speech Grounded in Social Theory with Diyi Yang and David Muchlinski

In this episode, Diyi Yang gives us an overview of using NLP models for social applications, including understanding social relationships, processes, roles, and power.  As NLP systems are getting used more and more in the real world, they additionally have increasing social impacts that must be studied.  We talk about how to get started in this field, what datasets exist and are commonly used, and potential ethical issues.  We additionally cover two of Diyi's recent papers, on neutralizing subjective bias in text, and on modeling persuasiveness in text.Diyi Yang is an assistant professor in the School of Interactive Computing at Georgia Tech.

In this episode, Diyi Yang gives us an overview of using NLP models for social applications, including understanding social relationships, processes, roles, and power. As NLP systems are getting used more and more in the real world, they additionally have increasing social impacts that must be studied. We talk about how to get started in this field, what datasets exist and are commonly used, and potential ethical issues. We additionally cover two of Diyi's recent papers, on neutralizing subjective bias in text, and on modeling persuasiveness in text. Diyi Yang is an assistant professor in the School of Interactive Computing at Georgia Tech.

119 - Social NLP, with Diyi Yang

Think about the most recent news headline you read. Was it completely objective, void of any presupposition of truth or language that may lead readers down one particular path of understanding? Or did it, more likely, contain subtle cues about how the message was being framed, casting doubt on its veracity or reliability. Every day, we are inundated with these types of texts that, on the surface, proclaim to be arbiters of truth but, due to simple word choice and message framing, can bias their consumers. Luckily, new tools are being developed to help us become more critical recipients of media. In this podcast, we chat with Diyi Yang about how artificial intelligence can help us identify this subjective bias in text – and how AI itself can reflect our own preexisting biases.

Will AI Help Identify Bias ... or Perpetuate It?, with Diyi Yang