Laura Moses

My core agenda investigates interest actors, who they are, and how they impact the political process. In my dissertation, I introduce the theoretical concept of interest actors as individuals, who are recognized by an audience and assume a valued role in politics, particularly in online social media spaces. I provide operational traction to interest actors by evidencing them on Twitter with machine learning and investigate how these interest actors can impact the content that Members of Congress share online, how they connect with interest groups and shape the digital public sphere.

This provides a new theory for conceptualizing elites online. Interest actors are valuable—indeed—critical, for comprehensively analyzing and understanding politics in a digital context. Their presence and behaviors online have implications for political activity, the digital public sphere, and participatory democracy.

I draw on machine learning, text methods, and networks to evidence interest actors and demonstrate their impacts in social and communications networks. Related work extends our understanding of interest actors with constructed political, social identities to develop a theory for the different types of interest actors and how they derive value from their audiences.

My methodological agenda develops and applies quantitative methods in pursuit of the above research, focusing on how we can incorporate the content and context of individual communications to advance our understanding of political influence. Drawing on information theory and computer science, I introduce measures that capture the time-sensitive influence actors can have on one another through speeches, audio, image, and text-based communications to create network representations of communications. This provides insights into who and how Members of Congress and interest actors are influenced. I have also applied these methods to state actors to evaluate states' influence in discussions of the United Nations Security Council.

I build our understanding of interest groups behaviors and effects in a digital political contexts. How are interest groups using these platforms and engaging online? I show that interest group networks use social platforms for informational exchanges but also form complex sociopolitical ties that better allow interest groups to connect with the public, gain symbolic representational benefits from follower ties, and diversify political involvement. Using machine learning to identify interest groups online, I evaluate their sociopolitical assoications with other organizations. Supplemented with interviews, I illustrate how interest groups use social media to frame issues, impact politics and explain how interest group connections online are important to understand democratic processes.

I developed collaborative projects with leading scholars that extend the communications and digital platforms research established in my dissertation. I examine congressional speech and the role of rhetoric to understand how members of Congress communicate with Janet M. Box-Steffensmeier. We published an article in Science Advances that measures tone in Facebook messages from members of the Congress and demonstrates partisan differences and a differential impact of tone on message engagement and information spread related to COVID-19. Working with a team of computational social science students, we consider how rhetoric, partisanship and language used in one-minute speeches to understand who is taking advantage of one-minute speeches and how topics and valence speeches evolve over time, and identify populism and anti-elite rhetoric in speech use. We have articles in preparation that evaluate the rhetorical relationships between members of Congress over time and the evolution of populist language in one minute speeches. Planned extensions of this work will connect this study of rhetoric, and populism to the full congressional record and incorporate the messaging and content of legislators from social media.

This project provides the a large-scale and systematic analysis of a range of factors that potentially contribute to receiving clemency from the President of the United States. We explore changes in presidential clemency over multiple administrations, and how presidents use pardons to advvance policies and examine strategies that include the traditional act of using the formal application process established within the Office of the Pardon Attorney, as well as more informal back-door routes.

I also research the links between political rhetoric and democratic civic practice using computational methods. I work with Janet M. Box-Steffensmeier, Dino Christenson, and Sahar Abi-Hassan and an interdisciplinary team of undergraduate research assistants to evaluate how rhetoric and narratives factor into elite decision-making, public opinion, and political outcomes. Projects span Congress, the executive branch, and courts, and draw data from the congressional record, news coverage of events, and amicus briefs.