Laura K. Nelson

Associate Professor of Sociology

University of British Columbia

Biography

I’m an associate professor of sociology at the University of British Columbia and am the director of the Centre for Computational Social Science. See this Q&A for more on my research, teaching, and what I hope to accomplish at UBC.

Previously, I was an assistant professor at Northeastern University, where I was core faculty at the NULab for Text, Maps, and Networks, a faculty affiliate at the Network Science Institute, and was a member of the executive committee of the Women’s, Gender, and Sexuality Studies Program.

I am elected council for the Sociology of Culture and the Mathematical Sociology sections of the American Sociological Association. I’m a consulting editor and an ad hoc deputy editor at the American Journal of Sociology and I’m on the editorial boards of Poetics and Acta Sociologica.

Interests

social movements
gender
computational sociology
text analysis
culture
institutions

Education

PhD in Sociology
University of California, Berkeley
MA in Sociology
University of California, Berkeley
BA in Sociology with a Concentration in Analysis and Research
University of Wisconsin, Madison

Skills

Python

R

Linux

Professional Appointments

Associate Professor of Sociology

University of British Columbia

Jul 2024 – Present Vancouver, BC

Director - Centre for Computational Social Science

Assistant Professor of Sociology

University of British Columbia

Jul 2021 – Jun 2024 Vancouver, BC

Director - Centre for Computational Social Science

Assistant Professor of Sociology

Northeastern University

Aug 2016 – Jun 2021 Massachusetts

Core Faculty - NULab for Texts, Maps, and Networks
Executive Committee - Women’s, Gender and Sexuality Studies Program
Affiliated Faculty - Network Science Institute

Postdoctoral Fellow

University of California, Berkeley

Aug 2016 – Aug 2017 California

Research Fellow - Berkeley Institute for Data Science
Research and Teaching Fellow - Digital Humanities @ Berkeley

Postdoctoral Research Fellow

Northwestern University

Aug 2014 – Aug 2016 Illinois

Research Fellow - Kellogg School of Management
Research Affiliate - Northwestern Institute on Complex Systems

Publications

Book Review: *The Ordinal Society* by Marion Fourcade and Kieran Healy

What does it mean for computers to intervene in the business of seeing and organizing society? The answer to this question in now more important than ever.

Laura K. Nelson

Book Review: *The Ordinal Society* by Marion Fourcade and Kieran Healy

Updating 'The Future of Coding': Qualitative Coding with Generative Large Language Models

This article tests the ability of generative LLMs to replicate and augment traditional qualitative coding, experimenting with multiple prompt structures across four closed- and open-source generative LLMs and proposing a workflow for conducting qualitative coding with generative LLMs.

Nga Than, Leanne Fan, Tina Law, Laura K. Nelson, Leslie McCall

Updating 'The Future of Coding': Qualitative Coding with Generative Large Language Models

From Funding Equity Initiatives to Research Productivity: Quantifying the Impact of NSF ADVANCE Awards on Recipients’ Publication Trajectories

Service work in academia, including organizational change efforts, often competes with time for research, potentially affecting academic careers (tenure, promotion, and pay) through slowed publication productivity. The authors examine changes in publication trajectories among academics participating in the National Science Foundation ADVANCE program, finding that scholars involved in ADVANCE awards published significantly more articles within the first four years after receiving funding.

Alexander J. Gates, Laura K. Nelson, Rachael Grudt, Kathrin Zippel

From Funding Equity Initiatives to Research Productivity: Quantifying the Impact of NSF ADVANCE Awards on Recipients’ Publication Trajectories

Translating Interdisciplinary Knowledge for Gender Equity: Quantifying the Impact of NSF ADVANCE

Interdisciplinarity is often hailed as a necessity for tackling real-world challenges. We examine the prevalence and impact of interdisciplinarity in the NSF ADVANCE program, finding ADVANCE publications exhibit higher levels of interdisciplinarity across three dimensions of knowledge integration. These findings emphasize the significance of interdisciplinarity in problem-oriented knowledge production, indicating that specific forms of interdisciplinarity can lead to broader impact.

Alexander J. Gates, Jessica R. Gold, Laura K. Nelson, Kathrin Zippel

Translating Interdisciplinary Knowledge for Gender Equity: Quantifying the Impact of NSF ADVANCE

Gender and Inconsistent Evaluations: A Mixed-methods Analysis of Feedback for Emergency Medicine Residents

Prior research has demonstrated that men and women emergency medicine (EM) residents receive similar numerical evaluations at the beginning of residency, but that women receive signiﬁcantly lower scores than men in their ﬁnal year. To better understand the emergence of this gender gap in evaluations we examined discrepancies between numerical scores and the sentiment of attached textual comments.

Alexandra Brewer, Laura K. Nelson, Anna S. Mueller, Rebecca Ewert, Daniel M. O'Connor, Arjun Dayal, Vineet M. Arora

Taking the Time: The Implications of Workplace Assessment for Organizational Gender Inequality

This paper examines gendered differences in workplace assessment in eight U.S. hospitals, finding that, compared to men, women attendings wrote more words in their comments to residents, used more job-related terms, and were more likely to provide helpful feedback, particularly when residents were struggling, while women residents were less likely to receive substantive evaluations.

Laura K. Nelson, Alexandra Brewer, Anna S. Mueller, Daniel M. O'Connor, Arjun Dayal, Vineet M. Arora

Taking the Time: The Implications of Workplace Assessment for Organizational Gender Inequality

Formally comparing topic models and human-generated qualitative coding of physician mothers’ experiences of workplace discrimination

Differences between computationally generated and human-generated themes in unstructured text are important to understand yet difficult to assess formally. In this study, we bridge these approaches, comparing topic models to hand-generated categories and comparing two different topic modelling solutions.

Adam S. Miner, Sheridan A. Stewart, Meghan C. Halley, Laura K. Nelson, Eleni Linos

Formally comparing topic models and human-generated qualitative coding of physician mothers’ experiences of workplace discrimination

From Ends to Means: The Promise of Computational Text Analysis for Theoretically Driven Sociological Research

In presenting the contributions to a special issue, we discuss several insights that emerge from this work, which hold relevance not only for current and aspiring practitioners of computational text analysis, but also for its skeptics.

Bart Bonikowski, Laura K. Nelson

From Ends to Means: The Promise of Computational Text Analysis for Theoretically Driven Sociological Research

Situated Knowledges and Partial Perspectives: A Framework for Radical Objectivity in Computational Social Science and Computational Humanities

Starting from the premise that objectivity in knowledge creation is a worthy—even utopian—pursuit, this essay argues that computational methods are aligned with embodied objectivity and the situated knowledges and partial perspectives framework proposed by Donna Haraway.

Laura K. Nelson

Situated Knowledges and Partial Perspectives: A Framework for Radical Objectivity in Computational Social Science and Computational Humanities

The NSF ADVANCE Network of Organizations

As the ADVANCE program celebrates its 20th anniversary, we describe the growth and composition of the organizational network over the past two decades to explore the breadth and reach of the ADVANCE program in the U.S. higher education system.

Jessica R. Gold, Alexander J. Gates, Syed A. Haque, Miranda C. Melson, Laura K. Nelson, Kathrin Zippel

The NSF ADVANCE Network of Organizations

And the Rest is History: Measuring the Scope and Recall of Wikipedia’s Coverage of Three Women’s Movement Subgroups

Narrating history is perpetually contested, shaping and reshaping how nations and people understand both their pasts and the current moment. Measuring and evaluating the scope of histories is methodologically challenging. In this paper we provide a general approach and a specific method to measure historical recall.

Laura K. Nelson, Rebekah Getman, Syed Arefinul Haque

And the Rest is History: Measuring the Scope and Recall of Wikipedia’s Coverage of Three Women’s Movement Subgroups

Leveraging the Alignment Between Machine Learning and Intersectionality: Using Word Embeddings to Measure Intersectional Experiences of the Nineteenth Century U.S. South

I empirically demonstrate the alignment between machine learning and inductive research through a word embedding model of first-person narratives of the nineteenth-century U.S. South.

Laura K. Nelson

Leveraging the Alignment Between Machine Learning and Intersectionality: Using Word Embeddings to Measure Intersectional Experiences of the Nineteenth Century U.S. South

From Theory to Practice and Back: How the Concept of Implicit Bias was Implemented in Academe, and What this Means for Gender Theories of Organizational Change

Using an inductive, theory-building approach and combination of computational and qualitative methods, we investigate how the concept of implicit bias was translated into practice through the ADVANCE program and identify five key features that made implicit bias useful as a change framework in the academic STEM setting.

Laura K. Nelson, Kathrin Zippel

From Theory to Practice and Back: How the Concept of Implicit Bias was Implemented in Academe, and What this Means for Gender Theories of Organizational Change

The Future of Coding: A Comparison of Hand-Coding and Three Types of Computer-Assisted Text Analysis Methods

This article compares three common computer-assisted approaches—dictionary, supervised machine learning, and unsupervised machine learning—to those produced through a rigorous hand-coding analysis of inequality in the news.

Laura K. Nelson, Derek Burk, Marcel Knudsen, Leslie McCall

The Future of Coding: A Comparison of Hand-Coding and Three Types of Computer-Assisted Text Analysis Methods

Computational Grounded Theory: A Methodological Framework

This article proposes a three-step methodological framework called computational grounded theory, which combines expert human knowledge and hermeneutic skills with the processing power and pattern recognition of computers, producing a more methodologically rigorous but interpretive approach to content analysis.

Laura K. Nelson

Computational Grounded Theory: A Methodological Framework

To Measure Meaning in Big Data, Don’t Give Me a Map, Give Me Transparency and Reproducibility

In an attempt to reorient the field toward a new standard for measuring meaning in big data, one based on transparency and replicability, I propose five guidelines to evaluate any text-analysis project.

Laura K. Nelson

Courses and Workshops

Accountable Computer Systems

This course brings together students from a diverse set of backgrounds who will learn from an equally diverse group of faculty and outside experts in law, computer science, public policy, artificial intelligence, digital records management and preservation, philosophy, and machine learning how to identify real problems that might require technical or partially-technical solutions, the language in which to communicate between multiple disciplines, and the possible approaches for addressing the most pressing challenges.

Word Embeddings for Social Scientists and Humanists

A workshop on word embeddings, to demystify some of the technical aspects of language models and to invite learners to start thinking about how these important tools function in society.

Analyzing Complex Digitized Data

Introduction to Python for the social sciences and humanities

Bostonography

The City through Data, Texts, Maps, and Networks

Computational Text Analysis for Humanists and Social Scientists

Material for a 3 day workshop on computational text analysis for humanists and social scientists

Data and Society

How data, algorithms, and AI shape and are shaped by society

Digital Humanities at Berkeley Summer Institute: Computational Text Analysis

Teaching material for a 2017 workshop in computational text analysis for humanists (and social scientists)

Encoding and Decoding when Working with Text

A short lesson on teaching text encoding to non-CS majors

Foundations of Social Theory II

Contemporary Social Theory, Graduate Level

Select Talks

Cycles of Conflict, a Century of Continuity: Computational Methods and the Longue Durée

Using computational methods to examine women’s movements from the 1860s to the 1970s, I challenge long-standing theories of feminist waves and reflect on the potential for using computational methods, in particular when combined with qualitative methods and interpretation, to re-examine historical patterns in social movements over long time frames.

Sep 9, 2022 9:00 PM — 10:30 PM Indiana University Workshop in Methods

Cycles of Conflict, a Century of Continuity: Computational Methods and the Longue Durée

Partial Perspectives and Situated Knowledge: Radical Objectivity using Computational Methods

In this talk I propose that, despite its claims to elevate social science to the level of the physical sciences, the social physics perspective as it is currently practiced produces a decidedly unscientific and unobjective approach to social science.

Dec 14, 2021 2:00 PM — 3:00 PM DSI Distinguished Speaker Series, Columbia University

Leveraging Machine Learning to Measure Intersectionality

I empirically demonstrate the alignment between machine learning and inductive analysis through a word embedding model of first-person narratives of the nineteenth-century U.S. South.

Mar 8, 2021 8:15 PM — 9:15 PM Harvard University, Inequality & Social Policy Seminar

Leveraging Machine Learning to Measure Intersectionality

Online Posts & Media

How do we nurture an academic landscape that is more accessible to women? Let’s start by getting rid of the in-person interview

In the lead up to International Women’s Day on Friday March 8th, SAGE Ocean posed a series of questions to leading academics. In this post I explores how we nurture an academic landscape that is more accessible to women.

The Computation/Context Trade-Off?

In this blog post I explore a fundamental question in computational social science: does “big computation” necessarily comes at the expense of narrative richness, contextual detail, and theory? Or, conversely, narrative richness can only happen without computation?

Developing a Feel It, Touch It, Smell It Analytics

Rather than simply calling for diversity within the field of data analytics on terms dictated by this “new ‘Old Boy Network’ of Ivy Leaguers,” we should instead make big data, and data analytics, work on our own terms. I believe we can develop a data analytics that helps us touch, smell, and feel the game (and the social world).

Feminism, Culture, and Computational Sociology

To give a taste of my research agenda I highlight below a few of my findings and methods, ending with hopes for future research along these lines.

Text as Data: A Call to Standardize Access and Training

Data come in all shapes and sizes, but in the past ten years we have seen huge leaps in the amount of data readily available in the form of unstructured or semi-structured text. This presents both opportunities and challenges for social science researchers, including social movements scholars.

Computer-Assisted Content Analysis and Sociology: What You Should Know

In this blog post I address two common critiques of computational text analysis, as they are articulated by Andrew Perrin, in his review of the Poetics special issue on topic modelling.

Contact

laura.k.nelson@ubc.ca
ANSO - 6303 NW Marine Dr, Vancouver, BC
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