Research Projects

Code we produce and publicly release is available in our Github repository: https://github.com/casmlab

Public Officials and Social Media

CaSM Team: Dr. Libby Hemphill, Dr. Jahna Otterbacher, Dr. Matthew Shapiro, Andrew Roback, Charise Angderson, Drexler James, Amy Paslak, W. David Work

Public officials are adopting social media at increasing rates, and this project aims to understand the impact of that adoption. Using data from Twitter, primarily, we explore how officials, both elected and appointed, frame issues such as climate change. We also study how social media use impacts communication with constituents and civic engagement. See the CaSM Lab Twitter lists page to see some of the officials we’re currently studying. Visit the Public Officials and Social Media project page for presentations and publications related to this research.

Understanding and Revealing Information Bias

CaSM Team: Dr. Libby Hemphill, Dr. Jahna Otterbacher, Charise Angderson, Erica Dekker, Aaron Samardzich, Cheng-Hsin Weng

The information we see online, especially in user-generated content communities, is necessarily biased. Our goal in this project is to understand how the presentation is biased, how the design of communities creates bias in information presentation, and how to make users aware of the biases at work. We don’t argue that all bias is bad, just that it should be clear to users how the information they’re viewing may be biased. In some cases, the bias is dangerous. For instance, in mixed-gender online communities, males typically enjoy more power and prestige than females. In this project, we analyze user contributions to review sites such as the Internet Movie Database (IMDb) and WebMD in order to understand the relationships between language use, gender, and the perceived value of users’ contributions. Collaborative filtering systems often rely on user feedback about utility to determine which content to suggest and make readily available. Because users rarely adjust the filters’ defaults or dig very deeply into contributed content, it’s important that we understand how users judge the value of others’ contributions and how contributors understand and act upon community feedback so that we may ensure diversity in both content and participation in online communities. Visit the Understanding and Revealing Information Bias project page for presentations and publications related to this research.

Temporary Collaborations in Knowledge Work

CaSM Team: Dr. Libby Hemphill
Collaborators: Dr. Stephanie Teasley (Michigan), Dr. Erik Johnston (ASU), Jennifer Auer (ASU)

One of NSF’s Virtual Organizations grants, this study focuses on post docs joining virtual science and engineering teams. With regard to post docs, the objectives of the project are (1) to better understand under what general conditions Post-Doctoral Fellows are successful and (2) to identify social and technical barriers for Post-Doctoral Fellows entering virtual organizations. We also view post docs as a particular kind of temporary knowledge workers who are highly-educated and possess incredibly specialized expertise. We use data from our post doc study to examine the impacts of ad hoc collaborative arrangements on knowledge workers more broadly.

Overherd: Information Visualizations in Online Discussion Forums

CaSM Team: Dr. Libby Hemphill, Ruoran Wang
Collaborators: Dr. Stephanie D. Teasley (Michigan), Dr. Kevin Nam (Lincoln Lab)

In the Overherd project, we’re studying how different visual representations of the data in online discussion forums can help readers understand the overall content and activity in the forum. Think about the last time you tried to understand whether you were in the right place on the Apple Support Forums to find the help you needed, or when you last used Yelp to find a restaurant but weren’t sure whether any of the reviews had recent information. These are the kinds of information problems we’re trying to address in the Overherd project.

You can learn more about Overherd at its own website, and you can download the current Overherd code from GitHub.

Social Networks and Cultural Production

CaSM Team: Dr. Libby Hemphill, Andrew Roback, Chris King

Social networks and social network analysis (SNA) are hot topics in research and public life. Our goal for projects in this area is to develop tools and methods that help make social network analysis accessible for non-experts so that we may leverage SNA to help society. For instance, we’re using IMDB data to explore ways for making social network data more easily translatable and to demonstrate user-friendly ways of conducting SNA. Dr. Hemphill’s affiliation with theĀ Social Media Research Foundation is integral to this project.

Sustainability Game Studies

CaSM Team: Dr. Libby Hemphill, Charise Angderson
Collaborators: Qian Hu (ASU), Dr. Erik W. Johnston (ASU), Dr. Ajay Vinze (ASU)

Humans are resource obese – our use of natural resources exceeds our need – and this gluttony has troubling consequences for the sustainability of worldwide economic health and quality of life. The Sustainability Game Studies (SGS) project explores how we may be able to use a collaborative simulation to understand and encourage sustainable decision making under uncertainty.