Fall 2020

Emory Sociology provides an extensive curriculum for our graduate students. Below are the topical courses and individualized programs offered in Fall 2020

Use the sidebar options to see our graduate course offerings in other semesters.

Research Methods and Models: Statistics (SOC 500) - Timothy J. Dowd

Wednesday 9:40am-12:40pm


Course Description:

This an introduction to descriptive and inferential statistics for bivariate and multivariate analyses. The course will help you understand statistics reported in social science publications and in the news media, as well as help you conduct original research. The overall goal is to increase your statistical literacy – your ability to create, interpret, present, and critically evaluate statistical evidence. This is a set of skills that you will find highly useful in your current academic life and in your future career. It is also a valuable set of skills for virtually everyone in modern society, as statistical knowledge (and numerical literacy more broadly) is key for making sense of the growing amounts of information that we encounter in a digital world.

Recommended (but Not Required) Texts:

  • Paul D. Allison. 1999. Multiple Regression: A Primer. Thousand Oaks, CA: Pine Forge.
  • Whitney Battle-Baptiste and Britt Rusert, Editors. 2018. W.E.B. Du Bois’s Data Portraits: Visualizing Black America. NY: Princeton Architectural Press.
  • Kieran Healy. 2019. Data Visualization: A Practical Introduction. Princeton, NJ: Princeton University Press.
  • Wendy Zeitlin and Charles Auerbach. 2019. Basic Statistics for the Behavioral and Social Scientists Using R. New York: Oxford University Press.

(Other chapters and articles will be available on the SOC 500 Canvas site during the semester.)

Research Methods and Models: Design (SOC 501) - Timothy J. Dowd

Monday 9:40am-12:40pm


Course Description: 

Mindful of current debates social science methodologies, the course takes a practical, “hands-on” approach to research methods. We begin with a consideration of the fundamental contributions of such scholars as W.E.B. Du Bois, Jane Addams, W.E.B. Du Bois, Max Weber, and Ida B. Wells. From there, we trace the proliferation of methodologies that have led to the mixed-methods and digital approaches of the present.

The current incarnation of this seminar also builds on how Dr. Irene Browne has taught it in previous semesters. Hence, with the assistance of the instructor, your advisor, and your peers, you will identify a research question that could develop into a viable second year paper. Through staged assignments throughout the semester, you will design a study to answer your research question, execute the study by collecting pilot data or downloading secondary data, and analyze your results. You will present these results in an empirical paper at the end of the semester. As a requirement for our class, you must become certified in human subjects research at Emory by taking the on- line CITI course by September 14.  

Recommended (but Not Required) Texts:

  • Eduardo Bonilla-Silva and Tukufu Zuberi. Editors. 2008. White Logic, White Methods: Racism and Methodology. Lanham, MD: Rowman & Littlefield.
  • Aldon D. Morris. 2015. The Scholar Denied: W.E.B. Du Bois and the Birth of Modern Sociology. Berkeley, CA: University of California Press.
  • National Science Foundation. 2008. Workshop on Interdisciplinary Standards for Systematic Qualitative Research. Report prepared by: Michèle Lamont, Harvard University; Patricia White, National Science Foundation for the National Science Foundation: Cultural Anthropology, Law and Social Science, Political Science, and Sociology Programs.
  • Matthew J. Salganik. 2019. Bit by Bit: Social Research in the Digital Age. Princeton, NJ: Princeton University Press.

(Other chapters and articles will be available on the SOC 501 Canvas site during the semester.)

Sociology of Health & Illness (SOC 531) - Ellen Idler

Tuesday 9:40am-12:40 pm


Course Description:

This course will provide graduate students with a survey of research on the social origins of the health, illness, and health care of individuals and populations. Students will be introduced to the process of formulating important social research questions in health and illness, including attention to major theoretical perspectives, measurement of concepts, the merits of various study designs, and both qualitative and quantitative approaches to data collection and analysis.

There are no assigned texts to order.

Racial & Ethnic Health Disparities (SOC 585) - Alyasah Sewell

Monday/Wednesday 4:20-5:35pm


Course Description:

This course provides a broad overview of ethnoracial health inequities. Despite medical advances over the past century, ethnoracially-marginalized people in the United States carry an unequal and inequitable burden of disease and dis-ease in the prisms of oppression. The elimination of health disparities have been a major focus of public policy as an orientation towards health equity and health justice have emerged as scaffolding constructs. This course covers provides a historical treatment of ethnoracial health inequities; lays forth the competing theoretical assumptions of health policy traditions; and excavates the social determinants of ethnoracial health inequities. Key structural and systemic foundations of ethnoracial health inequities are considered from a “womb to tomb” framework identifying the sociobiology of ethnoracisms that shape life and death. Students will conduct a critical empirical analysis describing the multidimensional and multilevel pathways by which ethnoracisms enter and leave the body and contribute to health inequities.

Required Texts:

Institute of Medicine. (2003) Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, D.C.: National Academies Press. (ISBN: 9780309082655)

LaVeist, Thomas and Lydia A. Isaac (2012). Race, Ethnicity and Health: A Public Health Reader. San-Francisco: Jossey-Bass. (ISBN: 9781118049082)

Washington, Harriet A. 2006. Medical Apartheid: The Dark History of Medical Experimentation on Black Americans from Colonial Times to the Present. New York: Doubleday Books. (ISBN: 9780385509930)


Big/Small Data & Visualization (SOC 585) - Roberto Franzosi

Tuesday/Thursday 8:00-9:15am


Course Description:

The course deals with new tools of data analysis and visualization, especially for text data (Natural Language Processing, NLP). It is a very demanding 4-credits course, fulfilling the writing requirement since it requires extensive weekly writing. The course does NOT require any prerequisites or prior knowledge of computational tools. The only requirement is that students come to the class with a corpus of data as txt formatted files (e,g, newspaper articles, books, blogs, websites) that they wish to analyze.

The course is based on a set of specialized NLP tools, written in Java and Python, designed for the analysis of small/large corpora of text.The tools are all wrapped in Python with a convenient Graphical User Interface (GUI) to make things easy for the non expert.

The course relies on the Stanford parser CoreNLP as the main NLP engine(with the option of running co-reference resolution), but a number of other NLP tools will also be usedto investigate the CoNLL table created by the CoreNLP parser for specific relationships between specific words, verb and noun density, “function” words, and automatic extraction of SVOs (Subject, Verb, Objects). Two specific tools for passive/active verb forms and nominalization allow to focus on the “denial of agency” at the linguistic level. Other tools focus on the sentiment and language concreteness of a text. The two tools of N-grams and word co-occurrences viewers mimic the behavior of Google N-Grams Viewer but with a personal corpus. Topic modeling, via Mallet or Gensim, allows users to find the main topics in a large set of documents. Word2Vec (via Gensim), a vector representation of words, can help capture the semantic regularities of a corpus.

The course also embeds easy tools of data visualization for a variety of Excel-type charts, network graphs, and Geographic Information System (GIS) maps. The course focuses on freeware software, from Gephi to Cytoscape, Palladio, Google Earth Pro, QGIS, Carto, TimeMapper.


Advanced Network Analysis (SOC 585) - Weihua An

Monday/Wednesday 6:00-7:15pm


Course Description:

Interest in network analysis has EXPLODED in the past few years, partly due to the latest advancements in statistical modeling and the rapid availability of network data and partly due to the recognition that many analytical problems can be re-cast as a network problem. Aiming to examine social connections and interactions quantitatively, network analysis has become an essential method and tool for studying a variety of issues in social and natural sciences. This course covers the major methods to collect, represent, and analyze network data. Selected topics include centrality analysis, positional analysis, clustering analysis, the exponential random graph model for modeling network formations, the stochastic actor-oriented model for dynamic network analysis, meta network analysis, weighted network analysis, text network analysis, causal analysis of network effects, and social network-based predictions and interventions. Examples are drawn from a wide range of disciplines including business, economics, education, political science, public health, and sociology. Students will learn hands-on skills to conduct their own research by using mainstream network packages in R such as “statnet” and “RSiena”. This course requires a basic knowledge of logistic regression and basic programming skills in R.

Recommended (Not Required) Textbooks:

  1. Wasserman, Stanley and Katherine L. Faust. 1994. Social Network Analysis: Methods and Applications. New York: Cambridge University Press. (ISBN- 978-0521387071)
  2. Lusher, D., Koskinen, J. & Robins, G. 2013. Exponential Random Graph Models for Social Networks: Theory, Methods, and Applications. Cambridge University Press. (ISBN- 978-0521141383)

Directed Study (SOC 597R or SOC 797R)

These offer credit for individualized work with a given faculty member.

Please consult with your advisor and / or Dr. Ellen Idler (our Director of Graduate Studies) about enrollment.

MA Research (SOC 599R) or PhD Research (SOC 799R)

These offer credit for ongoing research overseen by a given faculty member.

Please consult with your advisor and / or Dr. Ellen Idler (our Director of Graduate Studies) about enrollment.

Teaching Assistantships (TATT 605SOC & TATT 610SOC)

These offer credit for participation in assistantships (TATT 605C) and for teaching one's own class (TATT 610SOC).

Read more about these credits here.