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Associate Professor Sociology jsmith77@unl.edu (402) 472-3335 706 Oldfather Hall

Personal Website

Google Scholar 

Curriculum Vitae

Introduction and Current Research 

I joined the faculty at UNL in 2013, shortly after receiving my Ph.D. from Duke University. I am also affiliated with the Rural Drug Addiction Research Center (RDAR) at UNL. My research interests include social networks, quantitative methods, inequality and drug use. I have done methodological work on network sampling and missing data, as well as more substantive work on network processes like homophily and status. My work has been published in the American Sociological ReviewSociological MethodologySocial Networks, Social Science & Medicine, as well as other venues. You can find detailed information on my publications (including links to the papers) on my website, as well as from my Google Scholars page. My website also includes information about the courses I have taught, including all of the materials from a recent seminar on network analysis

My research explores methodological and substantive problems related to networks, individuals, and the broader social context. Methodologically, my work centers on a core problem in network studies: how can network structure be measured when there is incomplete information, either because there is missing data or because the data itself come from a sample. The larger agenda is to make it easier to specify and test theories based on a network view of the social world—where the complex interdependencies between actors are explicitly mapped, even with limited data.  For example, I am currently working on a project that uses sampled network data to make inference about diffusion processes. Substantively, my work pushes a contextual approach to studying social networks. The key question is how network features, like hierarchy, cohesion or group structure, vary across contexts, such as schools or neighborhoods. The larger goal is to analyze contexts, networks and individuals holistically: where contextual features, like demographic composition and economic inequality, shape network features, which, in turn, shape outcomes at the individual-level, like deviance or health.

 

I am also currently working on a new project on rural drug-use and networks. The NIH funded project will study the risk factors associated with rural drug use, looking at the social network dynamics and behavioral contexts that contribute to overdose risk and increased risk of addiction.

 

Student Opportunities

I am always looking for students to act as collaborators on projects related to networks, methods and social inequality. For example, I am currently collaborating with one graduate student (Sela Harcey) on a project that explores the effect of racial/ethnic classification on measures of stratification. We are also working on a project (with Robin Gauthier) on the relationship between isolation, cohesion and adolescent outcomes. I am also interested in collaborating with students with an interest in studying rural drug use, health risks and social networks.

 

 

Current Teaching

I have taught a number of different courses at UNL, many of them core methods courses: Introduction to Social Research II (an introductory, undergraduate statistics course); Advanced Regression Analysis (a graduate level course covering categorical models); Social Networks: Theory, Methods and Applications (a graduate level course in networks); History of Social Theory (a graduate theory course) and Social Inequality (an undergraduate course on inequality). These courses include a diverse set of students, ranging from undergraduates only (Introduction to Social Research II), to a mix of undergraduate and graduate students (Social Inequality), to graduate only (History of Social Theory). The courses I have taught are also quite diverse in terms of material: from very technical classes to very theoretical classes to substantive courses to a mixture.

 

Selected Publications

Substantive Network Papers

Smith, Jeffrey A. and Robert Faris. 2015. "Movement without mobility: Adolescent status hierarchies and the contextual limits of cumulative advantage." Social Networks 40:139-153

Smith Jeffrey A., McPherson, Miller, and Lynn Smith-Lovin.  2014. “Social Distance in the United States: Sex, Race, Religion, Age, and Education Homophily among Confidants, 1985 to 2004.” American Sociological Review 79:432-456.

McFarland, Daniel A., James Moody, David Diehl, Jeffrey A. Smith, and Reuben J. Thomas. 2014. "Network Ecology and Adolescent Social Structure." American Sociological Review 79:1088-1121.

Network Methods

Smith, Jeffrey A. and Jessica Burrow*. 2018. “Using Ego Network Data to Inform Agent-

Based Models of Diffusion.” Sociological Methods & Research. doi:10.1177/0049124118769100

 

Smith, Jeffrey A., James Moody and Jonathan H. Morgan. 2017. "Network Sampling Coverage II: The Effect of Non-Random Missing Data on Network Measurement." Social Networks 48:78-99. doi: http://dx.doi.org/10.1016/j.socnet.2016.04.005.

Smith, Jeffrey A. 2015. "Global Network Inference from Ego Network Samples: Testing a Simulation Approach." The Journal of Mathematical Sociology 39:125-162

Merli, M. Giovanna, James Moody, Jeffrey Smith, Jing Li, Sharon Weir, and Xiangsheng Chen. 2015. "Challenges to recruiting population representative samples of female sex workers in China using Respondent Driven Sampling." Social Science & Medicine 125:79-93

 

Recent Grant Activity

 

Rural Drug Addiction Center (Director: Kirk Dombrowski)

National Institute of Drug Abuse (NIDA)        

Grant no. 1P20GM130461-01

Center for Biomedical Research Excellence (P20)

Role: Early Career Project Leader

Project Title: Capturing Rural Injection Risk Networks from Continuous-time Interaction Data

 

Other Information

Service Roles

I am currently serving as a member of the advisory board for an NIH funded project on teaching network science in middle school. For more information and opportunities to get involved, please see: http://worldsofconnections.com/.

 

Ph.D. Duke University

Areas of Specialization:

  • Social Networks
  • Quantitative Methods
  • Computational Social Science
  • Inequality