Research Statement
My research builds on concepts and methods developed for the study of
social networks, statistics and demography. I have developed novel
methods for the integration of demographic processes to better
understand network evolution, and have also developed spatial models for
estimation and simulation of large-scale population level social
networks. In addition, I use methods for network measurement and data
collection on and offline. These activities and others have enabled my
systematic investigation of problems within the areas of sociology,
demography, statistics and social network analysis. My research sits at
the intersection of these fields.
Thematic Overview
Environmental Action and Governance
Funding
Articles
- Bagozzi, B. E., D. Berliner, and Z. W. Almquist (2021). When Does
Open Government Shut? Predicting Govern- ment Responses to Citizen
Information Requests. Regulation & Governance 15(2), 280–297.
- Almquist, Z.W. and B. E. Bagozzi (2020). Automated Text Analysis for
Understanding Radical Activism: The Topical Agenda of the North American
Animal Liberation Movement. Research and Politics 7(2), 1-8.
- Almquist, Z.W. and B. E. Bagozzi (2019). Using Radical Environmental
Texts to Uncover Network Structure and Network Features. Sociological
Methods & Research 48(4), 905–960.
- Almquist, Z.W. and B. E. Bagozzi (2016). The Spatial Properties of
Radical Environmental Organizations in the UK: Do or Die! PloS ONE
11(11), 1–19.
Epidemology and Public Health
COVID-19
Funding
- 2020-2021 Holland, J.H. (PI), Kline, M. (Co-PI),
Smaldino, P. (Co-PI), Moya, C. (Co-PI), and Almquist, Z.W. (Co-PI).
“RAPID: Coupled Contagion, Behavior-Change, and the Dynamics of Pro and
Anti-Social Behavior During the COVID-19 Pandemic.” Grant #BCS-2028160,
NSF,
Behavioral and Cognitive Sciences (BCS), Cultural Anthropology (CA).
$233,283.
Articles
- Loring J Thomas, Peng Huang, Fan Yin, Junlan Xu, Zack W Almquist,
John R Hipp, Carter T Butts (2022). “Geographical Patterns of Social
Cohesion Drive Disparities in Early COVID Infection Hazard”. Proceedings
of the National Academies of Sciences 119 (12).
- Thomas, L.J., P. Huang, F. Yin, X.I. Luo, Z.W. Almquist, J.R. Hipp,
and C.T. Butts (2020). Spatial Heterogeneity Can Lead to Substantial
Local Variations in COVID-19 Timing and Severity. Proceedings of the
National Academy of Sciences 117(39), 24180–24187.
- Jones, J. H., A. Hazel, and Z.W. Almquist (2020).
Transmission-Dynamics Models for the SARS Coronavirus-2. American
Journal of Human Biology 32(5), 1-14.
Spatial Demography & Social Networks
Homelessness
Funding
- 2022-2027 Almquist, Z.W. (PI). “CAREER: Measuring and
Modeling the Multi-Modal Networks and Demographics of People
Experiencing Homelessness.” Grant #SES-2142964, NSF
Social & Economic Sciences (SES), Sociology. $500,000.
- 2022-2023 Hagopian, A., Kajfasz, O., Zhao, B., Hebert,
P., Almquist, Z., Luo, G. and Dobra, A. “Innovating better methods to
enumerate individuals experiencing homelessness.” University of
Washington Population Health Initiative’s Tier 2 Pilot Grant with
support from CSDE and Department of Health Systems and Population
Health. $106,822.
- 2022-2023 de la Iglesia, H., Martin, M. and Almquist,
Z.W. “Sleep health in people experiencing homelessness.” University of
Washington Population Health Initiative’s Tier 1 Pilot Grant Program
with support from CSDE and the Department of Biology. $38,468.91.
Articles
- Anderson, M. C., A. Hazel, J. M. Perkins, and Z. W. Almquist (2021).
The Ecology of Unsheltered Homelessness: Environmental and
Social-Network Predictors of Well-Being among an Unsheltered Homeless
Population. International Journal of Environmental Research and Public
Health 18(14), 7328.
- Almquist, Z.W. (2020). Large-scale Spatial Network Models: An
application to modeling information diffusion through the homeless
population of San Francisco. Environment and Planning B: Urban Analytics
and City Science 47(3), 523–540.
- Almquist, Z.W., N. E. Helwig, and Y. You (2020). Connecting
Continuum of Care Point-in-Time Homeless Counts to United States Census
Areal Units. Mathematical Population Studies 27(1), 46–58.
Spatial Demography
Funding
- 2014-2015 Jack DeWaard (Co-PI) and Zack W. Almquist
(Co-PI). “Internal Migration and Recovery from the Great Recession in
Urban Minnesota Counties and Neighborhoods.” CURA Faculty Interactive Research
Program, University of Minnesota. $45,000.
Articles
- Thomas, L. J., P. Huang, F. Yin, J. Xu, Z. W. Almquist, J. R. Hipp,
and C. T. Butts (2022). Geographical Patterns of Social Cohesion Drive
Disparities in Early COVID Infection Hazard. Proceedings of the National
Academy of Sciences 119(22).
- Abel, G. J., J. DeWaard, J. Trang Ha, and Z. W. Almquist (2021). The
Form and Evolution of International Migra- tion Networks, 1960-2015.
Population, Space and Place 27(3), 1–15.
- Almquist, Z. W., T. D. Nguyen, M. Sorensen, X. Fu, and N. D.
Sidiropoulos (2021). Uncovering migration systems through
spatio-temporal tensor co-clustering. arXiv: 2112.15296.
- Maas, P, Almquist, Z.W., Giraudy, E. and Schneider, J. W. (2020).
Using social media to measure demographic responses to natural disaster:
Insights from a large-scale Facebook survey following the 2019 Australia
Bushfires. arXiv preprint arXiv:2008.03665.
- Thomas, L.J., P. Huang, F. Yin, X.I. Luo, Z.W. Almquist, J.R. Hipp,
and C.T. Butts (2020). Spatial Heterogeneity Can Lead to Substantial
Local Variations in COVID-19 Timing and Severity. Proceedings of the
National Academy of Sciences 117(39), 24180–24187.
- Almquist, Z.W. (2020). Large-scale Spatial Network Models: An
application to modeling information diffusion through the homeless
population of San Francisco. Environment and Planning B: Urban Analytics
and City Science 47(3), 523–540.
- Almquist, Z.W., N. E. Helwig, and Y. You (2020). Connecting
Continuum of Care Point-in-Time Homeless Counts to United States Census
Areal Units. Mathematical Population Studies 27(1), 46–58.
- Almquist, Z.W. and C. T. Butts (2012). Point process models for
household distributions within small areal units. Demographic Research
26 (22), 593–632.
- Almquist, Z.W. (2010). US Census Spatial and Demographic Data in R:
The UScensus2000 Suite of Packages. Journal of Statistical Software
37(6), 1–31.
Spatial Networks
Funding
Articles
- Thomas, L. J., P. Huang, F. Yin, J. Xu, Z. W. Almquist, J. R. Hipp,
and C. T. Butts (2022). Geographical Patterns of Social Cohesion Drive
Disparities in Early COVID Infection Hazard. Proceedings of the National
Academy of Sciences 119(22).
- Thomas, L.J., P. Huang, F. Yin, X.I. Luo, Z.W. Almquist, J.R. Hipp,
and C.T. Butts (2020). Spatial Heterogeneity Can Lead to Substantial
Local Variations in COVID-19 Timing and Severity. Proceedings of the
National Academy of Sciences 117(39), 24180–24187.
- Almquist, Z.W. (2020). Large-scale Spatial Network Models: An
application to modeling information diffusion through the homeless
population of San Francisco. Environment and Planning B: Urban Analytics
and City Science 47(3), 523–540.
- Almquist, Z.W. and B. E. Bagozzi (2016). The Spatial Properties of
Radical Environmental Organizations in the UK: Do or Die! PloS ONE
11(11), 1–19.
- Spiro, E.S., Z.W. Almquist, and C.T. Butts (2016). The Persistence
of Division: Geography, Institutions, and Online Friendship Ties.
Socius: Sociological Research for a Dynamic World 2(1), 1–15.
- Almquist, Z.W. and C. T. Butts (2015). Predicting Regional
Self-Identification from Spatial Network Models. Geographical Analysis
47(1), 50–72.
- Boessen, A., J.R. Hipp, E.J. Smith, C. T. Butts, N N. Nagle, and
Z.W. Almquist (2014). Networks, Space, and Residents’ Perception of
Cohesion. American Journal of Community Psychology 53(3), 447–461.
- Smith, E. J., C. S. Marcum, A. Boessen, Z.W. Almquist, J. R. Hipp,
N. N. Nagle, and C. T. Butts (2014). The Relationship of Age to Personal
Network Size, Relational Multiplexity, and Proximity to Alters in the
Western United States. The Journal of Gerontology: Series B 70(1),
91–99.
Health and Networks
Activity-Based Networks
Funding
Articles
- Almquist, Z.W., S. Arya, L. Zeng, and E. S. Spiro (2019). Unbiased
Sampling of Users from (Online) Activity Data. Field Methods 31(1),
23–38.
- Zeng, L., Z.W. Almquist, and E. S. Spiro (2019). “Friending” in
Online Fitness Communities: Exploring Activity-Based Online Network
Structure. In: Proceedings of the 52nd Hawaii International Conference
on System Sciences, pp.2822–2831.
- Zeng, L., Z.W. Almquist, and E. S. Spiro (2018). Stay Connected and
Keep Motivated: Modeling Activity Level of Exercise in an Online Fitness
Community. In: Social Computing and Social Media. Technologies and
Analytics. Ed. by G. Meiselwitz. Vol. 10914. Lecture Notes in Computer
Science. Springer International Publishing, pp.137–147.
- Zeng, L., Z.W. Almquist, and E. S. Spiro (2017). Let’s Workout!
Exploring Social Exercise in an Online Fitness Community. In: The
iConference 2017 Proceedings, Wuhan, China. Vol. 2, pp.87–98.
Mental Health and Network Models
Funding
Articles
- Anderson, M. C., A. Hazel, J. M. Perkins, and Z. W. Almquist (2021).
The Ecology of Unsheltered Homelessness: Environmental and
Social-Network Predictors of Well-Being among an Unsheltered Homeless
Population. International Journal of Environmental Research and Public
Health 18(14), 7328.
- Anker, J.J., M. Forbes, Z.W. Almquist, J. Menk, P. Thuras, and M. G.
Kushner (2017). A Network Approach to Conceptualizing Comorbid
Internalizing and Alcohol Use Disorders. Journal of Abnormal Psychology
126(3), 325–339.
- Boessen, A., J.R. Hipp, E. J. Smith, C. T. Butts, N. N. Nagle, and
Z.W. Almquist (2014). Networks, Space, and Residents’ Perception of
Cohesion. American Journal of Community Psychology 53(3), 447–461.
Organizational Networks
Funding
Articles
- Almquist, Z.W., E. S. Spiro, and C. T. Butts (2016). “Shifting
Attention: Modeling Follower Relationship Dynamics among US Emergency
Management-related Organizations During a Colorado Wildfire”. In: Social
Network Analysis of Disaster Response, Recovery, and Adaptation. Ed. by
A. Faas and E. Jones. Philadelphia, PA: Elsevier.
- Almquist, Z.W. and B. E. Bagozzi (2016). The Spatial Properties of
Radical Environmental Organizations in the UK: Do or Die! PloS ONE
11(11), 1–19
- Almquist, Z.W. and C. T. Butts (2013). Dynamic Network Logistic
Regression: A Logistic Choice Analysis of Inter- and Intra-group Blog
Citation Dynamics in the 2004 US Presidential Election. Political
Analysis 21(4), 430–448.
Methodology
Statistics
Funding
Articles
- Mallik, A. and Z.W. Almquist (2019). Stable Multiple Time Step
Simulation/Prediction from Lagged Dynamic Network Regression Models.
Journal of Computational and Graphical Statistics 28(4), 967-979.
- Almquist, Z.W. and C. T. Butts (2018). Dynamic Network Analysis with
Missing Data: Theory and Methods. Statistica Sinica 28(3),
1245–1264.
- Meeden, G., Z. Almquist, and C. Geyer (2016). Better adjusted
weights for respondents in skewed popula- tions. In: Proceedings of
Statistics Canada Symposium 2016.
- Almquist, Z.W. and C. T. Butts (2014). “Bayesian Analysis of Dynamic
Network Regression with Joint Edge/Vertex Dynamics”. In: Bayesian
Inference in the Social Sciences. Ed. by I. Jeliazkov and X.-S. Yang.
Hoboken, New Jersey: John Wiley & Sons.
- Almquist, Z.W. (2010). US Census Spatial and Demographic Data in R:
The UScensus2000 Suite of Packages. Journal of Statistical Software
37(6), 1–31.
Temporal Networks
Funding
- 2014-2017 Zack W. Almquist (PI). “Scalable Temporal
Network Models with Population Dynamics: Estimation, Simulation, and
Prediction.” Award #W911NF-14-1-0577, Young Investigator Program, Army Research
Office. $146,079.
- 2013-2014 Carter T. Butts (PI) and Zack W. Almquist
(Co-PI). “Doctoral Dissertation Research: Dynamic Network Models for the
Scalable Analysis of Networks with Missing or Sampled Joint Edge/Vertex
Evolution.” Grant #SES-1260798, NSF
Social & Economic Sciences, Methodology, Measurement and
Statistics. $15,140.
Articles
- Mallik, A. and Z.W. Almquist (2019). Stable Multiple Time Step
Simulation/Prediction from Lagged Dynamic Network Regression Models.
Journal of Computational and Graphical Statistics 28(4), 967-979.
- Almquist, Z.W. and C. T. Butts (2018). Dynamic Network Analysis with
Missing Data: Theory and Methods. Statistica Sinica 28(3),
1245–1264.
- Almquist, Z.W., E. S. Spiro, and C. T. Butts (2016). “Shifting
Attention: Modeling Follower Relationship Dynamics among US Emergency
Management-related Organizations During a Colorado Wildfire”. In: Social
Network Analysis of Disaster Response, Recovery, and Adaptation. Ed. by
A. Faas and E. Jones. Philadelphia, PA: Elsevier.
- Butts, C. T. and Z.W. Almquist (2015). A Flexible Parameterization
for Baseline Mean Degree in Multiple-Network ERGMs. The Journal of
Mathematical Sociology 39(3), 163–167.
- Almquist, Z.W. and C. T. Butts (2014). “Bayesian Analysis of Dynamic
Network Regression with Joint Edge/Vertex Dynamics”. In: Bayesian
Inference in the Social Sciences. Ed. by I. Jeliazkov and X.-S. Yang.
Hoboken, New Jersey: John Wiley & Sons.
- Almquist, Z.W. and C. T. Butts (2014). Logistic Network Regression
for Scalable Analysis of Networks with Joint Edge/Vertex Dynamics.
Sociological Methodology 44(1), 273–321.
- Almquist, Z.W. and C. T. Butts (2013). Dynamic Network Logistic
Regression: A Logistic Choice Analysis of Inter- and Intra-group Blog
Citation Dynamics in the 2004 US Presidential Election. Political
Analysis 21(4), 430–448.
Sampling and Measurement
Sampling
Funding
- 2022-2023 Williams, N., Almquist, Z.W., Crowder, K.,
Curran, S., Ellis, M. Herting, J., and Louie, P. “Feasibility Study for
Puget Sound Longitudinal Health and Wellbeing Data Project: Sound Data
for a Healthy Sound”. Royalty Research Fund (RRF), University of
Washington. $39,192.
- 07/2014 Zack W. Almquist (PI) and Glen Meeden
(Co-PI). “A Bayesian Approach to Finite Population Sampling for the
Social Sciences: Applications to Sample Weighting and Small Area
Estimation.” Population
Center Proposal Development Grant, University of Minnesota.
$8,000.
Articles
- Nilakanta, H., Z.W. Almquist, and G. L. Jones (2019). Ensuring
Reliable Monte Carlo Estimates of Net- work Properties. arXiv preprint
arXiv:1911.08682.
- Almquist, Z.W., S. Arya, L. Zeng, and E. S. Spiro (2019). Unbiased
Sampling of Users from (Online) Activity Data. Field Methods 31(1),
23–38.
- Meeden, G., Z. Almquist, and C. Geyer (2016). Better adjusted
weights for respondents in skewed popula- tions. In: Proceedings of
Statistics Canada Symposium 2016.
- Kurant, M., M. Gjoka, Y. Wang, Z.W. Almquist, C. T. Butts, and A.
Markopoulou (2012). Coarse-Grained Topology Estimation via Graph
Sampling. In: Proceedings of ACM SIGCOMM Workshop on Online Social
Networks (WOSN) ’12. Helsinki, Finland.
Network Measurment
Funding
Articles
- Almquist, Z.W. and B. E. Bagozzi (2019). Using Radical Environmental
Texts to Uncover Network Structure and Network Features. Sociological
Methods & Research 48(4), 905–960.
- Almquist, Z.W. (2012). Random errors in egocentric networks. Social
Networks 34(4), 493–505.
Text and Networks
Funding
Articles
- Bagozzi, B. E., D. Berliner, and Z.W. Almquist (forthcoming). When
Does Open Government Shut? Predicting Government Responses to Citizen
Information Requests. Regulation & Governance.
- Almquist, Z.W. and B. E. Bagozzi (2020). Automated Text Analysis for
Understanding Radical Activism: The Topical Agenda of the North American
Animal Liberation Movement. Research and Politics 7(2), 1-8.
- Almquist, Z.W. and B. E. Bagozzi (2019). Using Radical Environmental
Texts to Uncover Network Structure and Network Features. Sociological
Methods & Research 48(4), 905–960.