Research Topics
What is more important to a blossoming friendship: identifying with the same racial background or sharing the same tastes in music? What types of preferences are most likely to “spread” through social ties—or cause your friends to run in the opposite direction? Do friends tend to resemble one another because “similarity breeds attraction” or because friends become more similar over time? These seemingly basic questions have been notoriously difficult to answer because they require detailed data on both individual characteristics and social relationships (and how “tastes” as well as “ties” evolve over time). Data from the ubiquitous social network website Facebook—combined with recent advances in network modeling—create new opportunities for addressing these puzzles.
Research Collaborator:
Andreas Wimmer
From academic papers to the popular press, there has been a great deal of enthusiasm behind the potential for social media to revolutionize civic engagement—and a few scattered dissenters. Rarely, however, is either type of claim substantiated with systematic evidence. The Save Darfur Cause on Facebook provides a striking illustration of internet “slacktivism” at its most extreme: Among the 1.2 million members of this massive online movement, only a fraction engaged in any meaningful behavior (whether social recruitment or financial donation) beyond the basic act of joining. In other words, Facebook enabled an “army of armchair activists” rather than facilitating any deep or sustained commitment to this social cause.
Research Collaborators:
Kurt Gray | Jens Meierhenrich
Mating patterns have long been considered an optimal barometer of intergroup relations: Who is willing and unwilling to mate with whom can tell us a great deal about the types of social cleavages (e.g., racial, socioeconomic, religious) that characterize a given society. While most sociological research on mate choice has focused on marriage records, these data provide only a limited window into the complex, dynamic, and potentially asymmetric forces that lead to romantic coupling. Meanwhile, online dating is a phenomenon that has skyrocketed in popularity, and data from these sites have the potential to surmount a number of limitations of prior work—providing an unprecedented look at how social boundaries are enacted and eroded in the earliest stages of finding a partner.
Just as contemporary advances in technology have transformed social interaction, so too have they provided exciting new opportunities for social scientists. New datasets that are larger and more detailed than ever before—and are often collected in “natural” electronic settings without researcher intervention—are providing scholars with a fresh take on classic sociological questions. As more and more researchers and institutions dedicate time and resources to studying digital data, however, it is important that we are mindful of both the strengths and limitations of this approach; the latter have received comparatively little attention.
Research Collaborators:
Amir Goldberg | Daniel McFarland
Science advances through human cooperation. This cooperation occurs on a variety of levels (e.g. between individuals and institutions, strangers and colleagues) and has been measured in diverse ways (qualitative as well as quantitative). Network analyses of scientific collaboration typically focus on patterns of citation or co-authorship among researchers. Two other data sources provide new perspectives on scientific cohesion, fragmentation, and exclusion: acknowledgments in academic papers (documenting informal assistance in the form of feedback or support) and doctoral committee appointments (useful for addressing multiple topics in the sociology of higher education).
Research Collaborators:
Jordan Packer
Other publications and works-in-progress—using a diverse array of methods—address a variety of largely unrelated questions: Is it possible (and useful) to quantify free thought? Do people still form groups in the absence of differentiating characteristics? Why do gang members murder one another? What are the basic properties of digital communication? How long is the STEM “pipeline,” which fields and jobs are in it, and what happens to workers who “leak”?
Research Collaborators:
Kurt Gray | Mark Pachucki | John Skrentny | Andrew Papachristos