Institute for Computational and Experimental Research in Mathematics (ICERM)

Abstract

This tutorial provides an overview of some concepts, tools, and approaches relevant to quantitative work in the social justice sphere. We will work together to answer questions like the following: What does research at the interface of data science and social justice even look like? What are the theoretical underpinnings of this work? How can one acquire, clean, explore, visualize, and analyze relevant data? What are typical technical and theoretical challenges a researcher might encounter? What does ethical research look like? What opportunities exist for mathematical sciences researchers to apply their skills to promote justice?

Abstract

This tutorial provides an overview of some concepts, tools, and approaches relevant to quantitative work in the social justice sphere. We will work together to answer questions like the following: What does research at the interface of data science and social justice even look like? What are the theoretical underpinnings of this work? How can one acquire, clean, explore, visualize, and analyze relevant data? What are typical technical and theoretical challenges a researcher might encounter? What does ethical research look like? What opportunities exist for mathematical sciences researchers to apply their skills to promote justice?

Abstract

Each group leader will be given 15 minutes to introduce their project.

Abstract

Networks can be used to study and create models of social, engineering, and biological systems. In this tutorial I will introduce basic concepts and methods of network analysis and provide some examples of simple social system models. Some of the topics that will be discussed are methods of representing networks, basic characteristics of network structure, tutorials on importing network datasets and generating synthetic networks, and examples of various social contagion models. The goal of this tutorial is to give the audience the tools to create and explore basic models of social dynamics on synthetic or existing network datasets.

• Video
• Slides

Abstract

Networks can be used to study and create models of social, engineering, and biological systems. In this tutorial I will introduce basic concepts and methods of network analysis and provide some examples of simple social system models. Some of the topics that will be discussed are methods of representing networks, basic characteristics of network structure, tutorials on importing network datasets and generating synthetic networks, and examples of various social contagion models. The goal of this tutorial is to give the audience the tools to create and explore basic models of social dynamics on synthetic or existing network datasets.

• Video
• Slides

Abstract

40 minutes for talk & 20 minutes for discussion
In the summer of 2020, a large subset of the mathematical community agreed to boycott collaboration with the police. But how exactly have mathematicians collaborated with the police? In this talk, I will present a selective overview of predictive policing and predicting police, with a focus on network approaches, ranging from social network analysis of crime to network models of police misconduct, with a view towards a critical mathematical theory of policing. In doing so, I will make the case that there remains much interesting and urgent work to be done in this space.

• Video

Abstract

40 minutes for talk & 20 minutes for discussion
What is data feminism? How is feminist thinking being incorporated into data-driven work? And how are scholars in the humanities and social sciences, in particular, bringing together data science and feminist theory in their research? Drawing from her recent book, Data Feminism (MIT Press, 2020), coauthored with Catherine D’Ignazio, Klein will present a set of principles for doing data science that are informed by the past several decades of intersectional feminist activism and critical thought. In order to illustrate these principles, she will focus on a recent research project which involves the development of a model of lexical semantic change that, when combined with network analysis, tells a new story about antislavery activism and interracial solidarity (or the difficulties thereof) in the nineteenth-century United States. This example demonstrates how feminist thinking can indeed be operationalized into more ethical, more intentional, and more capacious data practices--particularly with respect to networks--in the digital humanities, computational social science, and beyond.

• Video Available Soon

Abstract

40 minutes for talk & 20 minutes for discussion
How has public discourse changed on Twitter over the COVID-19 pandemic? This talk will offer two case studies: the first on #MyBodyMyChoice, a hashtag originally created to advocate for women's rights but that has now drifted towards conversations around Covid-19, and the second on how advocates for Black maternal health changed the focus of their tweets over the pandemic. co-presented by Diana Grigsby, Justin Uhr, Shahrzad Haddadan, Bjorn Sandstede

• Video

Abstract

40 minutes for talk & 20 minutes for discussion
The Center for Digital Scholarship at Brown University offers hands-on instruction on a variety of digital scholarship methodologies, including network analysis, and this presentation will offer a snapshot of our services. First, we will share one of the ways we introduce students to network analysis. Next, this presentation will demo how we have used network analysis for one of our projects, Stolen Relations: Recovering Stories of Indigenous Enslavement in the Americas, which is led by Professor Linford Fisher (Department of History, Brown University). The Stolen Relations project is a community-based effort to build a database of enslaved Indigenous people in order to promote greater understanding of the historical circumstances and ongoing trauma of settler colonialism. The team has used the biographical information related to enslaved Indigenous people to chart networks and relations. These are hard realities and difficult histories, but they need to be told fully so we can start to be more honest about the history of this country and think more clearly about how to make amends going forward. Network analysis is one such way we can tell part of this story.

Abstract

40 minutes for talk & 20 minutes for discussion
We synthesize ideas and experience from research coordination networks to discuss how to foster success for the future of social justice research involving data science and computational methods. Together, we will lead discuss goals for the collaboration network. To achieve those goals, we consider conversations that the community should have as they move towards collaborative teams, introducing tools and techniques for both team communication and computational collaboration. We also ask that individuals reflect on how their personal goals and strengths will help the research team and the network.