University of Maryland

SoDa Seed Grant Series: Socio-Algorithmic Foundations of Trustworthy Recommendations

Date: February 13, 2024

Time: 12:00pm – 1:00pm

Location: Zoom

Registration coming soon!

SoDa Seed Grant Award Recipient:  Giovanni Luca Ciampaglia, Assistant Professor, College of Information Studies, University of Maryland

Industry Expert Guest Speaker: TBD

Abstract: Social media newsfeeds shape what people see online but, due to the interplay between human and algorithmic bias, these systems often amplify low-quality information, like misinformation and conspiracy theories. For example, prior work has shown that ranking the news by (either predicted or achieved) popularity can be problematic for partisan news consumers, as it creates a self-sustaining cycle that prioritizes pro-attitudinal information regardless of quality. How can we recommend reliable, trustworthy information on social media? My previous research has demonstrated that this cycle can be broken by prioritizing content that generates engagement in a politically diverse audience. However, the precise link between actual engagement, recommendation, and pro-attitudinal preferences is still unclear. The key question is how manipulations in news recommendation algorithms that promote news sources with diverse news audiences influence the information diets of users. To address this question, it is necessary to have access to a realistic social media environment where one can examine the impacts of rankings on news trustworthiness and consumption, and novel recommendation strategies for including audience signals into content rankings. The proposed work is, therefore, two-pronged: (1) Complete development of the Rockwell app (an innovative simulated social media environment designed in my lab) and (2) Conduct high-validity experiments to determine the influence of recommendation algorithms that incorporate signals related to audience diversity. Taken together, these activities will advance the theoretical and empirical understanding of the interaction between algorithmic curation and human news consumption decisions.

SoDa Seed Grants: The projects under this initiative may address any societal challenge that affects a large number of people, including but not limited to health, public safety, justice, race, gender, education, employment, transit, and political representation.  The goal of these seed grants is to encourage faculty to develop collaborative projects that stimulate the advancement of new ideas that can build the university’s expertise toward a national reputation in the broad area of social data science. The projects blend the development or use of innovative data science methods or new measurements, the advancement of scholarship within or across disciplines, and progress in addressing a societal challenge. 

The SoDa Center at UMD SoDa Symposia highlight the diverse challenges and opportunities in the emerging area of Social Data Science.   Combining insights of SoDa researchers and partners from UMD and around the world, these regular virtual events showcase research and expert commentary about advances and open problems in the use of surveys, administrative, and trace data to understand and shape the social world we live in. Ranging from technical challenges of gathering high-quality data, ethical management of social data at scale, or examples of the power of social data science in education, business, government, or civic life, SoDa Symposia provide an opportunity for a broad audience of researchers, students, and practitioners to learn more about the potential of social data science to change the world.