Ph.D. Research Reception

Presentations

Tracking Economic Development using Remote Sensing and Machine Learning

Satej Soman

The availability of high-resolution satellite imagery, providing a continuously-updated birds-eye view of the Planet Earth, has unlocked new applications in the physical and social sciences over the last three decades. In particular, the application of machine learning (ML) algorithms to remotely-sensed data has been used to predict a wide range of human development indicators at a relatively fine-grained scale. These highly-accurate and low-cost predictions have yet to be widely incorporated into decision-making despite their utility in resource-constrained settings where traditional approaches to measuring well-being may be infeasible. This talk discusses two projects focused on operationalizing the outputs of these prediction pipelines: 1) ongoing work with government agencies and development organizations in Nepal to explore how these estimates can complement traditional methods of census planning and survey design, and 2) experiments in West Africa and South Asia that test whether these estimation techniques can infer living standards and consumption levels at the spatial scale of individual households.

The Road Less Traveled: Characterizing Technologists within Nonprofit, Civil Society, and Advocacy Organizations

Lauren Chambers

A new class of data professionals is shaping policy, informing legal arguments, and bolstering advocacy efforts from inside nonprofit and civil society organizations. This career path might be claimed by a number of different new sociotechnical domains: public interest technology (PIT), civic technology, data for good, technology for social justice, and others. Yet it is still unclear exactly what professional roles are emerging, what sorts of people are filling them, and what such individuals’ work looks like and achieves. This work presents an interview study that seeks to characterize a specific sub-population of technological practitioners who are contributing materially to mission-driven projects from within the civil society or nonprofit sector: advocacy technologists. I present four patterns common to advocacy technologists: their disposition as skeptics who interrogate technological paradigms and moralists who prioritize ethical considerations, and their professional positioning as translators bridging technical and non-technical worlds and trailblazers forging new career paths. These four patterns point both to a strongly held dissatisfaction with the normative technology career path, and to the growing relevance of computational expertise within modern advocacy work. This study offers a nuanced understanding of advocacy technologists’ unique position and influence, contributing to the growing body of literature in human-computer interaction (HCI) and computer-supported cooperative work (CSCW) that explores computing technologies’ role in processes of sociopolitical change. Ultimately, these findings underscore the need for further research and more robust pipelines, in order to better understand and support advocacy technologists who are pursuing critical sociotechnical work beyond the private sector.

The Peripatetic Hater: Predicting Movement Among Hate Subreddits

Dan Hickey

Many online hate groups exist to disparage others based on race, gender identity, sex, or other characteristics. The accessibility of these communities allows users to join multiple types of hate groups (e.g., a racist community and a misogynistic community), raising the question of whether users who join additional types of hate communities could be further radicalized compared to users who stay in one type of hate group. However, little is known about the dynamics of joining multiple types of hate groups, nor the effect of these groups on peripatetic users. We develop a new method to classify hate subreddits and the identities they disparage, then apply it to understand better how users come to join different types of hate subreddits. We find distinct clusters of subreddits targeting various identities, such as racist subreddits, xenophobic subreddits, and transphobic subreddits. We show that when users become active in their first hate subreddit, they have a high likelihood of becoming active in additional hate subreddits of a different category. We also find that users who join additional hate subreddits, especially those of a different category, develop a wider hate group lexicon. These results then lead us to train a model that, as we demonstrate, usefully predicts the hate categories in which users will become active based on the text of posts they write and reply to. The accuracy of this model may be partly driven by peripatetic users often using the language of hate subreddits they eventually join. Overall, these results highlight the unique risks associated with hate communities on a social media platform, as discussion of alternative targets of hate may lead users to target more protected identities.

Social Styles: Computationally Modeling Website Styles as Sociolinguistic Variables

Naitian Zhou

Sociolinguistics is eminently concerned with the study of social meaning contained in style, where we take style to mean a coherent set of linguistic features which, together, convey or construct a social identity. In this on-going work, we study the mechanisms behind this meaning-making process with a large-scale computational analysis that focuses on visual style instead of linguistic style, identifying the social meanings present in the stylistic language of public-facing websites as expressed through CSS styles. We present a set of case studies that demonstrate how people use stylistic choices on their websites to convey information about themselves.

Use of Writing in the Visualization Design Process

Chase Stokes

This project explores the role of written language in visualization design, introducing the concept of a “writing rudder” as a guiding tool for designers. While sketching and wire-framing are well-established techniques for creating visualizations, writing is rarely considered part of the design process. However, in other creative domains, from essay writing to research planning, written language is a powerful tool for structuring ideas, clarifying intent, and guiding decision-making. Through two interview studies, we investigate how visualization designers engage with writing and explore different ways it might support their work. By framing writing rudders as a lightweight but structured intervention, we highlight its potential to shape visualization design in productive ways.