About

Christopher McCarty, Ph.D., is a Professor of Anthropology and the Associate Dean of the College of Liberal Arts and Sciences at the University of Florida. He serves as the Director of the UF Bureau of Economic and Business Research and has a background in cultural anthropology with a specialization in social network analysis. His research focuses on social network analysis, personal network analysis, collaboration networks, acculturation, disasters, and survey research. McCarty is widely recognized in the field of social network analysis for his expertise in applying personal network analysis to a broad range of topics, including substance abuse, addiction, and immigrant transnationalism. He developed the open source software program Egonet, which is extensively used by researchers across multiple disciplines, particularly in health care research. McCarty has contributed significantly to methods for collecting and analyzing personal network data and has applied these methods to various substantive research problems, including migrant studies, disaster response, hypertension, and scientific collaboration. He also co-developed the Network Scale-up Method (NSUM), a technique for estimating the size of hard-to-count populations, which has been adopted internationally for public health research. As the director of the UF Survey Research Center, he has overseen large-scale survey projects and contributed to survey methodology, especially in estimating populations and response rate analysis. His work integrates social network analysis with survey research, disaster studies, and health research, making him a prominent figure in these interdisciplinary fields.

Research topics

• Sociology
• Computer Science
• Political Science
• Social Science
• Artificial Intelligence
• Information Retrieval
• Biology
• Pedagogy
• Geography
• Statistics
• Engineering ethics
• Mathematics
• Epistemology
• Economic geography
• Engineering
• Psychology
• Data science
• Demography
• Ecology
• Gender studies
• Library science

Selected publications

• Replication data for: Comparing name generator designs in rural panel studies

  Zenodo (CERN European Organization for Nuclear Research) · 2026-04-08

  datasetOpen accessSenior author

  Abstract We conducted a two-wave personal network study in a rural Romanian community, interviewing the same participants (n = 68) using two name generators. Wave 1 employed a fixed-choice generator (n = 25) focused on emotional closeness; Wave 2 used a free-choice generator based on frequent interaction. We compared tie characteristics and assessed re-elicitation across waves. Alters who were kin, co-residents, or emotionally close were more likely to be re-elicited, regardless of generator type. These findings underscore the role of relational attributes in personal network elicitation and highlight design considerations for network studies in resource-limited, culturally distinct settings. Key-words: personal networks, name generators, rural fieldwork, tie retention, panel studies, longitudinal design This data package corresponds to the paper "Comparing name generator designs in panel personal network data: implications for alter re-elicitation in a rural field setting" (by MG Hâncean, J Lerner, C McCarty). The data were produced within the 4P-CAN project, HORIZON-MISS-2022-CANCER-01, project ID 101104432, programme HORIZON https://4p-can.eu/ This data package includes personal network information collected across two survey waves (Wave 1 and Wave 2). The study tracks focal participants (“egos”) and the individuals they name as social contacts (“alters”). There are 68 egos (study participants or cases) within the data package. Three data files are included in the present data package: Wave 1 (Wave 1 information; myData1.rds), Wave 2 (Wave 2 information; myData2.rds) and a data file that includes measurements from Wave 1 and Wave 2 (myData.rds). Each data file includes detailed information about egos and their alters, such as demographic characteristics (age, sex, education), family ties, co-residence, and interaction features such as closeness, meeting frequency, and relationship status Key features: • Ego-level variables include age, sex, and education; • Alter-level variables include age, sex, education, relationship to the ego, and co-residence; • Dyadic attributes include closeness, meeting frequency, and relationship status; • Metadata include wave information, operator (interviewer) ID, and retention status across waves. This data package is structured to support the replication of the analysis reported in the manuscript "Comparing name generator designs in panel personal network data: implications for alter re-elicitation in a rural field setting" (by MG Hâncean, J Lerner, C McCarty). For the code, check the Supplementary Material ("supplementary_material_updated.html"). "Comparing name generator designs in panel personal network data: implications for alter re-elicitation in a rural field setting" (by MG Hâncean, J Lerner, C McCarty) is available as part of the "Replication data for: Comparing name generator designs in rural panel studies", MG Hâncean, J Lerner, C McCarty. Zenodo DOI: https://doi.org/10.5281/zenodo.15322439 (2026). Unlike the previous version, the current version includes updated versions of the supplementary material and README note. We note that the data files are the same as in the previous version of the "Replication data for: Comparing name generator designs in rural panel studies". This data package also includes the files used for the additional analyses (i.e., myData1_ego.rds, alterDataW11.rds, mynet_participants11.rds, myattr_participants.rds). All the files included in this data package are available in the .rds file format. These can be manipulated using RStudio (version 2024.12.1+563). For further details, please check the README file.

  PublisherDOI

• Replication data for: Comparing name generator designs in rural panel studies

  Zenodo (CERN European Organization for Nuclear Research) · 2026-02-12

  datasetOpen accessSenior author

  Abstract We conducted a two-wave personal network study in a rural Romanian community, interviewing the same participants (n = 68) using two name generators. Wave 1 employed a fixed-choice generator (n = 25) focused on emotional closeness; Wave 2 used a free-choice generator based on frequent interaction. We compared tie characteristics and assessed re-elicitation across waves. Alters who were kin, co-residents, or emotionally close were more likely to be re-elicited, regardless of generator type. These findings underscore the role of relational attributes in personal network elicitation and highlight design considerations for network studies in resource-limited, culturally distinct settings. Key-words: personal networks, name generators, rural fieldwork, tie retention, panel studies, longitudinal design This data package corresponds to the paper "Comparing name generator designs in panel personal network data: implications for alter re-elicitation in a rural field setting" (by MG Hâncean, J Lerner, C McCarty). The data were produced within the 4P-CAN project, HORIZON-MISS-2022-CANCER-01, project ID 101104432, programme HORIZON https://4p-can.eu/ This data package includes personal network information collected across two survey waves (Wave 1 and Wave 2). The study tracks focal participants (“egos”) and the individuals they name as social contacts (“alters”). There are 68 egos (study participants or cases) within the data package. Three data files are included in the present data package: Wave 1 (Wave 1 information; myData1.rds), Wave 2 (Wave 2 information; myData2.rds) and a data file that includes measurements from Wave 1 and Wave 2 (myData.rds). Each data file includes detailed information about egos and their alters, such as demographic characteristics (age, sex, education), family ties, co-residence, and interaction features such as closeness, meeting frequency, and relationship status Key features: • Ego-level variables include age, sex, and education; • Alter-level variables include age, sex, education, relationship to the ego, and co-residence; • Dyadic attributes include closeness, meeting frequency, and relationship status; • Metadata include wave information, operator (interviewer) ID, and retention status across waves. This data package is structured to support the replication of the analysis reported in the manuscript "Comparing name generator designs in panel personal network data: implications for alter re-elicitation in a rural field setting" (by MG Hâncean, J Lerner, C McCarty). For the code, check the Supplementary Material ("supplementary_material_updated.html"). "Comparing name generator designs in panel personal network data: implications for alter re-elicitation in a rural field setting" (by MG Hâncean, J Lerner, C McCarty) is available as part of the "Replication data for: Comparing name generator designs in rural panel studies", MG Hâncean, J Lerner, C McCarty. Zenodo DOI: https://doi.org/10.5281/zenodo.18620321 (2026). Unlike the previous version, the current version includes updated versions of the supplementary material and README note. We note that the data files are the same as in the previous version of the "Replication data for: Comparing name generator designs in rural panel studies". This data package also includes the files used for the additional analyses (i.e., myData1_ego.rds, alterDataW11.rds, mynet_participants11.rds, myattr_participants.rds). All the files included in this data package are available in the .rds file format. These can be manipulated using RStudio (version 2024.12.1+563). For further details, please check the README file.

  PublisherDOI

• Time poverty and disaster readiness: How routine constraints shape hurricane preparation

  International Journal of Disaster Risk Reduction · 2026-01-31

  articleOpen accessSenior author

  Disaster warnings offer critical lead time for preparation, but how people use it is shaped by their daily routines and demands. Although prior research has examined psychological and demographic vulnerabilities in disaster preparedness, the impact of time-poverty – especially during back-to-back disasters – has received little attention. As a result, some groups may experience heightened time stress, lack sufficient time to prepare, or even face increased safety risks. Thus, we conducted an in-depth investigation of time poverty and time use in hurricane preparation, focusing on Florida communities affected by at least one of the consecutive 2024 hurricanes, Helene and Milton. Using geographically targeted surveys from 1,069 hurricane-affected residents, we examined how time poverty, employment status, family responsibilities, and socio-economic vulnerability influenced time use, perceived time insufficiency, and time stress. Latent Class Analysis identified five routine time-poverty profiles, including Young Time-Balanced Workers, Time-Rich Retired, Affluent Professionals, Working Overloaded Caregivers, and Strained Low-Income Caregivers . Moderated regression analyses revealed that time-poor caregivers and busy professionals experienced significantly greater time stress and completed fewer preparations, while those with flexible routines reported less stress. We also found that perceived timely warnings alleviated time insufficiency, but this benefit diminished with the onset of the second hurricane. Despite less time spent on preparation and fewer uncompleted tasks, participants reported higher time stress for the second event. Our findings highlight the need for targeted, timely alerts and institutional measures, such as flexible work arrangements and caregivers support, to address structural time poverty and improve disaster readiness, especially under compound disasters.

  PublisherDOI

• Collecting a large number of alters in egocentric network research: a comparative analysis of three approaches

  2025-02-15

  preprint

  This article presents an analysis of the impact of the number of alters elicited in an ego network on the structural properties of those networks. There continues to be debate about the pros and cons of eliciting a fixed number of alters for each respondent versus allowing the respondent to list as many or few alters as they would like. This article explores a random assignment of respondents to three treatment groups – 1) a fixed number of alters set at 30, 2) a variable number of alters up to 45, and 3) a variable number of alters up to 45 with a 20 alter minimum. The results indicate that, from a non-structural perspective, all levels of emotional proximity, interaction contexts, genders, and ages are consistently sampled across the three treatment groups. At the structural level, the behavior of individual metrics is also largely similar. However, the most significant differences arise in the collective behavior of structural metrics—specifically, in their correlation structure, the amount of redundant information each variable provides, and the diversity and interpretability of the observed structural variability. When a data collection strategy constrains network size, it reduces the sparsity of the correlation matrix, effectively decreasing the number of independent global variables needed to describe network structure and making these global variables less interpretable. In other words, networks constructed with a survey that limits size tend to be more similar to each other, exhibiting less structural diversity and yielding differences that are harder to interpret. However, we discuss how these differences may simply be mathematical artifacts, without necessarily implying a clear advantage in choosing one treatment over another. Finally, we argue that the field needs a targeted study to answer whether the differing numbers of alters listed is a function of network size.

  PublisherDOI

• Time Poverty and Disaster Readiness: How Routine Constraints Shaped Hurricane Preparation?

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Time Poverty and Disaster Readiness: How Routine Constraints Shaped Hurricane Preparation?

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• What is missing from this picture? Persistent homology and mixup barcodes as a means of investigating negative embedding space

  ArXiv.org · 2025-10-16

  preprintOpen accessSenior author

  Recent work in the information sciences, especially informetrics and scientometrics, has made substantial contributions to the development of new metrics that eschew the intrinsic biases of citation metrics. This work has tended to employ either network scientific (topological) approaches to quantifying the disruptiveness of peer-reviewed research, or topic modeling approaches to quantifying conceptual novelty. We propose a combination of these approaches, investigating the prospect of topological data analysis (TDA), specifically persistent homology and mixup barcodes, as a means of understanding the negative space among document embeddings generated by topic models. Using top2vec, we embed documents and topics in n-dimensional space, we use persistent homology to identify holes in the embedding distribution, and then use mixup barcodes to determine which holes are being filled by a set of unobserved publications. In this case, the unobserved publications represent research that was published before or after the data used to train top2vec. We investigate the extent that negative embedding space represents missing context (older research) versus innovation space (newer research), and the extend that the documents that occupy this space represents integrations of the research topics on the periphery. Potential applications for this metric are discussed.

  PublisherOA PDFDOI

• Socioeconomic inequalities in social support: Examining differences in social support network satisfaction and composition among pediatric cancer caregivers

  Journal of Psychosocial Oncology · 2025-03-27 · 1 citations

  article

  PURPOSE: Social support is an important factor in shaping healthcare navigation, coping, and psychological outcomes among pediatric cancer caregivers. Socioeconomic status is positively associated with satisfaction with social support, however, less is understood about network features that contribute to these differences. Social networks are the context in which resources and support are exchanged. Networks can exacerbate inequalities by amplifying differences in access to resources. We examined satisfaction with types of social support and composition of support networks among pediatric cancer caregivers to understand how social network dynamics differ by caregiver income and educational attainment. DESIGN: Participants were caregivers of children who received cancer treatment at multiple hospital systems in New York State. All families who met eligibility requirements during the recruitment period were invited to participate in the study, and 59% of caregivers contacted enrolled in the study. We used a self-report survey to collect egocentric social network data from 107 caregivers of pediatric cancer patients. We used bivariate logistic regression to examine differences in network support by income and education. We used Bayesian Zero and One Inflated Beta (ZOIB) regression models to examine differences in network composition by income and education. RESULTS: Income was significantly associated with satisfaction with informational, emotional, and logistical support; and for each additional income category the odds of reporting being satisfied with each type of support increased by nearly 1.5 times. There were also differences in satisfaction with informational support by education, and each additional education category was associated with a nearly 2-fold increased likelihood of satisfaction. Caregivers with higher education reported a relatively lower proportion of family/kin in their network and a relatively greater proportion of health care providers, compared to those with less education. CONCLUSIONS: Our results show differences in social support satisfaction and social network composition by income and education among pediatric cancer caregivers. These results have implications for improving intervention. Creating interventions to foster social network ties and activate social support may be a promising direction for promoting health equity.

  PublisherDOI

• Collecting a large number of alters in egocentric network research: a comparative analysis of three approaches

  2025-09-04

  articleOpen access

  This article presents an analysis of the impact of the number of alters elicited in an ego network on the structural properties of those networks. There continues to be debate about the pros and cons of eliciting a fixed number of alters for each respondent versus allowing the respondent to list as many or few alters as they would like. This article explores a random assignment of respondents to three treatment groups – 1) a fixed number of alters set at 30, 2) a variable number of alters up to 45, and 3) a variable number of alters up to 45 with a 20 alter minimum. The results indicate that, from a non-structural perspective, all levels of emotional proximity, interaction contexts, genders, and ages are consistently sampled across the three treatment groups. At the structural level, the behavior of individual metrics is also largely similar. However, the most significant differences arise in the collective behavior of structural metrics—specifically, in their correlation structure, the amount of redundant information each variable provides, and the diversity and interpretability of the observed structural variability. When a data collection strategy constrains network size, it reduces the sparsity of the correlation matrix, effectively decreasing the number of independent global variables needed to describe network structure and making these global variables less interpretable. In other words, networks constructed with a survey that limits size tend to be more similar to each other, exhibiting less structural diversity and yielding differences that are harder to interpret. However, we discuss how these differences may simply be mathematical artifacts, without necessarily implying a clear advantage in choosing one treatment over another. Finally, we argue that the field needs a targeted study to answer whether the differing numbers of alters listed is a function of network size.

  PublisherOA PDFDOI

• Comparing name generator designs in rural panel studies: analyzing alter retention and change

  ArXiv.org · 2025-06-11

  preprintOpen accessSenior author

  We conducted a two-wave personal network study in a rural Romanian community, interviewing the same participants (n = 68) using two name generators. Wave 1 employed a fixed-choice generator (n = 25) focused on emotional closeness; Wave 2 used a free-choice generator based on frequent interaction. We compared tie characteristics and assessed retention across waves. Alters who were kin, co-residents, or emotionally close were more likely to be retained, regardless of generator type. These findings underscore the role of relational attributes in personal network stability and highlight design considerations for network studies in resource-limited, culturally distinct settings.

  PublisherOA PDFDOI

Recent grants

• Development of a Social Network Measure of Acculturation and its Application to Immigrant Populations in South Florida and Northeastern Spain

  NSF · $150k · 2004–2006

• Social Network Analysis of the Collaborative Interaction of Scientists in Academic and Non-academic Settings

  NSF · $356k · 2007–2010

Frequent coauthors

• Peter D. Killworth

  National Oceanography Centre

  21 shared

• H. Russell Bernard

  Arizona State University

  20 shared

• Gene A. Shelley

  Centers for Disease Control and Prevention

  16 shared

• José Luís Molina

  Universitat Autònoma de Barcelona

  15 shared

• Eugene C. Johnsen

  University of California, Santa Barbara

  14 shared

• Raffaele Vacca

  University of Florida

  11 shared

• Miranda J. Lubbers

  11 shared

• Connie J. Mulligan

  University of Florida

  10 shared

Education

• PhD, Anthropology

  University of Florida

  1992

• MA, Anthropology

  University of Florida

  1985

• BA, Anthropology

  West Virginia University

  1980

Awards & honors

• Co-organizer Sunbelt Social Networks Conference (2008, 2011,…
• NIH Social Networks and Health panelist (2011-2012)
• NSF Program Officer for Cultural Anthropology (2013-2014)