What we do

Social Data Science at Arizona State University's New College helps promote a critical understanding of the ethical uses of social data, automation, and artificial intelligence, through leading-edge research, collaboration with a range of communities, and educating professionals and researchers.

Research

Our research is transdisciplinary, drawing on data science approaches to understanding social systems, applying social theory to understand how data is used and misused in society, and helping form practices and policies the promote the liberation of knowledge and people.

Collaboration

We work with faculty and students from across ASU to build a common understanding of how social data science can and should be used in a range of fields and professions. Our work is done in the context of multiple communities and publics, locally and globally.

Learning

Through our online Master's program and courses and workshops for students, professionals, and wider community, we foster mastery of the theories and tools that allow us to understand and to change the networked society.

Affiliated Researchers

Our group includes faculty and students from across ASU and beyond. The core faculty are listed below, or click for a full listing of affiliates.

Alexander Halavais

Associate Professor

datafication, creative communities, autonomy

Nicholas Proferes

Associate Professor

information, technology, social media

Seth Rachlin Headshot

Seth Rachlin

Assistant Teaching Professor

social & economic change

Shawn Walker

Assistant Professor

online resistance, protests, social media, archiving, social media methods

Recent Research

The Data & Society Program produces a broad range of research related to datafication and social change. Links to more research can be found on our Publications page.

A dynamic analysis of conspiratorial narratives on Twitter during the pandemic

C Shao, KH Kwon, S Walker, Q Li

Since the breakout of COVID-19 in late 2019, various conspiracy theories have spread widely on social media and other channels, fueling misinformation about the origins of COVID-19 and the motives of those working to combat it. This study analyzes tweets (N = 313,088) collected over a 9-month period in 2020, which mention a set of well-known conspiracy theories about the role of Bill Gates during the pandemic.
Link

Know (ing) Infrastructure: The Wayback Machine as object and instrument of digital research

J Ogden, E Summers, S Walker

From documenting human rights abuses to studying online advertising, web archives are increasingly positioned as critical resources for a broad range of scholarly Internet research agendas. In this article, we reflect on the motivations and methodological challenges of investigating the world’s largest web archive, the Internet Archive’s Wayback Machine (IAWM). Using a mixed methods approach, we report on a pilot project centred around documenting the inner workings of ‘Save Page Now’ (SPN) – an Internet Archive tool that allows users to initiate the creation and storage of ‘snapshots’ of web resources.
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The development of privacy norms

N Proferes

This chapter addresses how we develop, revisit, and negotiate norms around privacy when confronted with new technologies. The chapter first examines Nissenbaum’s (Washington Law Review 79 (1): 119–157, 2004) theory of privacy as contextual integrity, a framework that helps unpack how context-relevant norms for appropriateness and transmission can be challenged by new technologies. It then reviews how social norms develop as we build mental models of how a technology works during its diffusion process.
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Algorithmic inference, political interest, and exposure to news and politics on Facebook

Kjerstin Thorson, Kelley Cotter, Mel Medeiros & Chankyung Pak

How does Facebook algorithmically infer what users are interested in, and how do interest inferences shape news exposure?
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What COVID-19 dashboards aren’t telling us

Michael Simeone, Gracie Valdez, & Shawn Walker

These graphics and interactives are supposed to help us get a better understanding of the state of the pandemic. But too often, they offer incomplete pictures.
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Researcher views and practices around informing, getting consent, and sharing research outputs with social media users when using their public data

Nicholas Proferes & Shawn Walker

Publicly accessible social media data is frequently used for scientific research. However, numerous questions remain regarding what ethical obligations researchers have in regard to using such content.
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News

Recent and upcoming events and information
Machine learning graphic

Machine Learning Day 2023

ASU’s annual Machine Learning Day will once again be hosted by the B2C2 initiative on West Campus, Friday, April 9. It brings together scholars from across multiple fields who make use of ML in their Read more…