Bruce A Desmarais
Biographic Data
| ID | 635804 |
|---|---|
| NAME | Bruce A Desmarais |
| GIVEN NAMES | Bruce A |
| FAMILY NAME | Desmarais |
| SIGNATURE | DESMARAIS B A |
| AFFILIATIONS | Pennsylvania State University |
| VERIFIED | No |
| TOTAL WORKS | 28 |
| TOTAL CITATIONS | 570 |
| AUTHOR COUNT | 28 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2011 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 10 |
Elected officials’ Online Sharing of Misinformation: Institutional and Ideological Checks
Elected officials occupy privileged positions in public communication about important topics – roles that extend to the digital world. In the same way that public officials stand to lead constructive online dialogue, they also hold the potential to accelerate the dissemination of harmful content. We explore and explain the sharing of misinformation, which we refer to as low-factual content, by examining nearly 500,000 Facebook posts by U.S. state…
Networks of inclusion: Using teams and technology to create diverse social capital
Official yet questionable: Examining misinformation in U.S. state legislators’ tweets
We study the roles of elected officials in the dissemination of misinformation on Twitter. This is a particularly salient online population since elected officials serve as primary sources of information for many stakeholders in the public, media, government, and industry. We analyze the content of tweets posted from the accounts of over 3,000 U.S. state lawmakers throughout 2020 and 2021. Specifically, we identify the dissemination of URLs linke…
A Diffusion Network Event History Estimator
Research on the diffusion of political decisions across jurisdictions typically accounts for units’ influence over each other with (1) observable measures or (2) by inferring latent network ties from past decisions. The former approach assumes that interdependence is static and perfectly captured by the data. The latter mitigates these issues but requires analytical tools that are separate from the main empirical methods for studying diffusion. A…
A double-edged sword: The conditional properties of elite network ties in the financial sector
Existing scholarship suggests a deep relationship between elite connections and policy making in the financial sector. But are elite ties between private industry and government a resource for private industry, or a liability? We find that they can be either, depending on the circumstances. We analyze the associations of elite ties within numerous policy-making processes in the financial sector by measuring the network closeness between firms and…
Attention to the Covid‐19 Pandemic on Twitter: Partisan Differences Among U.S. State Legislators
Subnational governments in the United States have taken the lead on many aspects of the response to the COVID‐19 pandemic. Variation in government activity across states offers the opportunity to analyze responses in comparable settings. We study a common and informative activity among state officials—state legislators’ attention to the pandemic on Twitter. We find that legislators’ attention to the pandemic strongly correlates with the number of…
The contagion of democracy through international networks
Speaking truth in power: Scientific evidence as motivation for policy activism
Unelected administrative policymakers rely on the domain expertise and technical integrity of scientific information to maintain perceptions of legitimacy. The necessity that regulatory policymakers rely on sound scientific evidence has been formalized at the US federal level through executive order. Yet, the practical impact of scientific evidence on public support and mobilization for policies remains unclear. We investigate whether individual …
Considering Network Effects in the Design and Analysis of Field Experiments on State Legislatures
Recent work on legislative politics has documented complex patterns of interaction and collaboration through the lens of network analysis. In a largely separate vein of research, the field experiment—with many applications in state legislatures—has emerged as an important approach in establishing causal identification in the study of legislative politics. The stable unit treatment value assumption (SUTVA)—the assumption that a unit's outcome is u…
Temporal Exponential Random Graph Models with btergm: Estimation and Bootstrap Confidence Intervals
The xergm package is an implementation of extensions to the exponential random graph model (ERGM). It acts as a meta-package for multiple constituent packages. One of these packages is btergm, which implements bootstrap methods for the temporal ERGM estimated by maximum pseudolikelihood. Here, we illustrate the temporal exponential random graph model and its implementation in the package btergm using data on international alliances and a longitud…
Models, methods and network topology: Experimental design for the study of interference
Public Comments’ Influence on Science Use in U.S. Rulemaking: The Case of EPA’s National Emission Standards
Scholarship on bureaucratic policymaking has long focused on both the use of expertise and public accountability. However, few have considered the degree to which public input affects the use of research in U.S. regulatory impact analyses (RIAs). We examine changes in the research that is cited in RIAs in response to public comments to assess the influence of participation on the use of information for rulemaking. We conduct an in-depth analysis …
Stochastic weighted graphs: Flexible model specification and simulation
What Can We Learn from Predictive Modeling
The large majority of inferences drawn in empirical political research follow from model-based associations (e.g., regression). Here, we articulate the benefits of predictive modeling as a complement to this approach. Predictive models aim to specify a probabilistic model that provides a good fit to testing data that were not used to estimate the model’s parameters. Our goals are threefold. First, we review the central benefits of this under-util…
A Critique of Dyadic Design
Dyadic research designs concern data that comprise interactions among actors. They are, without a doubt, the most frequent designs employed in the empirical analysis of international politics. But what do such designs carry with them in terms of theoretical claims and statistical problems? These two issues closely intertwine. When testing hypotheses empirically, the statistical model must be a careful operationalization of the theory under consid…
Science Use in Regulatory Impact Analysis: The Effects of Political Attention and Controversy
Scholars, policy makers, and research sponsors have long sought to understand the conditions under which scientific research is used in the policy-making process. Recent research has identified a resource that can be used to trace the use of science across time and many policy domains. U.S. federal agencies are mandated by executive order to justify all economically significant regulations by regulatory impact analyses (RIAs), in which they prese…
The Fates of Challengers in U.S. House Elections: The Role of Extended Party Networks in Supporting Candidates and Shaping Electoral Outcomes
Extended party network (EPN) theory characterizes political parties in the United States as dynamic networks of interest groups that collaboratively support favored candidates for office. Electoral predictions derived from EPN theory have yet to be tested on a large sample of races. We operationalize EPNs in the context of organized interest contributions to U.S. House campaigns. We deduce that support by a partisan community of interests signals…
Persistent Policy Pathways: Inferring Diffusion Networks in the American States
The transmission of ideas, information, and resources forms the core of many issues studied in political science, including collective action, cooperation, and development. While these processes imply dynamic connections among political actors, researchers often cannot observe such interdependence. One example is public policy diffusion, which has long been a focus of multiple subfields. In the American state politics context, diffusion is common…
Measuring legislative collaboration: The Senate press events network
Public policy's bibliography: The use of research in US regulatory impact analyses
Major US federal regulatory decisions are developed and justified using regulatory impact analyses (RIAs) mandated by executive order. We examine the scientific citation activity in RIAs, a unique effort that we believe holds significant potential for understanding the use of science in policymaking. This paper reports preliminary findings from collecting and examining scientific citations in 104 RIAs from 2008–2012. We present evidence indicatin…
Reciprocity and the structural determinants of the international sanctions network
Complex Dependencies in the Alliance Network
The multifaceted and strategic interactions inherent in the formation of international military pacts render the alliance decisions of states highly interdependent. Our aim here is to model the network of alliances in such a way as to capture the effects of covariates and account for the complex dependencies inherent in the network. Regression analysis, due to its foundational assumption of conditional independence, cannot be used to analyze alli…
Toward a Network Theory of Alliance Formation
We propose a network-based theory of alliance formation. Our theory implies that, in addition to key state and dyad attributes already established in the literature, the evolution of the alliance network from any given point in time is largely determined by its structure. Specifically, we argue that closed triangles in the alliance network—where i is allied with j is allied with k is allied with i — produce synergy effects in which state-level ut…
Lessons in disguise: Multivariate predictive mistakes in collective choice models
Comparing Partial Likelihood and Robust Estimation Methods for the Cox Regression Model
The Cox proportional hazards model is ubiquitous in time-to-event studies of political processes. Plausible deviations from correct specification and operationalization caused by problems such as measurement error or omitted variables can produce substantial bias when the Cox model is estimated by conventional partial likelihood maximization (PLM). One alternative is an iteratively reweighted robust (IRR) estimator, which can reduce this bias. Ho…
Inferential Network Analysis with Exponential Random Graph Models
Methods for descriptive network analysis have reached statistical maturity and general acceptance across the social sciences in recent years. However, methods for statistical inference with network data remain fledgling by comparison. We introduce and evaluate a general model for inference with network data, the Exponential Random Graph Model (ERGM) and several of its recent extensions. The ERGM simultaneously allows both inference on covariates …
Persistent Policy Pathways: Inferring Diffusion Networks in the American States
The transmission of ideas, information, and resources forms the core of many issues studied in political science, including collective action, cooperation, and development. While these processes imply dynamic connections among political actors, researchers often cannot observe such interdependence. One example is public policy diffusion, which has long been a focus of multiple subfields. In the American state politics context, diffusion is common…
Complex Dependencies in the Alliance Network
The multifaceted and strategic interactions inherent in the formation of international military pacts render the alliance decisions of states highly interdependent. Our aim here is to model the network of alliances in such a way as to capture the effects of covariates and account for the complex dependencies inherent in the network. Regression analysis, due to its foundational assumption of conditional independence, cannot be used to analyze alli…
Micro‐Level Interpretation of Exponential Random Graph Models with Application to Estuary Networks
The exponential random graph model (ERGM) is an increasingly popular method for the statistical analysis of networks that can be used to flexibly analyze the processes by which policy actors organize into a network. Often times, interpretation of ERGM results is conducted at the network level, such that effects are related to overall frequencies of network structures (e.g., the number of closed triangles in a network). This limits the utility of …
A Critique of Dyadic Design
Dyadic research designs concern data that comprise interactions among actors. They are, without a doubt, the most frequent designs employed in the empirical analysis of international politics. But what do such designs carry with them in terms of theoretical claims and statistical problems? These two issues closely intertwine. When testing hypotheses empirically, the statistical model must be a careful operationalization of the theory under consid…
Toward a Network Theory of Alliance Formation
We propose a network-based theory of alliance formation. Our theory implies that, in addition to key state and dyad attributes already established in the literature, the evolution of the alliance network from any given point in time is largely determined by its structure. Specifically, we argue that closed triangles in the alliance network—where i is allied with j is allied with k is allied with i — produce synergy effects in which state-level ut…
The Fates of Challengers in U.S. House Elections: The Role of Extended Party Networks in Supporting Candidates and Shaping Electoral Outcomes
Extended party network (EPN) theory characterizes political parties in the United States as dynamic networks of interest groups that collaboratively support favored candidates for office. Electoral predictions derived from EPN theory have yet to be tested on a large sample of races. We operationalize EPNs in the context of organized interest contributions to U.S. House campaigns. We deduce that support by a partisan community of interests signals…
What Can We Learn from Predictive Modeling
The large majority of inferences drawn in empirical political research follow from model-based associations (e.g., regression). Here, we articulate the benefits of predictive modeling as a complement to this approach. Predictive models aim to specify a probabilistic model that provides a good fit to testing data that were not used to estimate the model’s parameters. Our goals are threefold. First, we review the central benefits of this under-util…
Public policy's bibliography: The use of research in US regulatory impact analyses
Major US federal regulatory decisions are developed and justified using regulatory impact analyses (RIAs) mandated by executive order. We examine the scientific citation activity in RIAs, a unique effort that we believe holds significant potential for understanding the use of science in policymaking. This paper reports preliminary findings from collecting and examining scientific citations in 104 RIAs from 2008–2012. We present evidence indicatin…
Attention to the Covid‐19 Pandemic on Twitter: Partisan Differences Among U.S. State Legislators
Subnational governments in the United States have taken the lead on many aspects of the response to the COVID‐19 pandemic. Variation in government activity across states offers the opportunity to analyze responses in comparable settings. We study a common and informative activity among state officials—state legislators’ attention to the pandemic on Twitter. We find that legislators’ attention to the pandemic strongly correlates with the number of…
Public Comments’ Influence on Science Use in U.S. Rulemaking: The Case of EPA’s National Emission Standards
Scholarship on bureaucratic policymaking has long focused on both the use of expertise and public accountability. However, few have considered the degree to which public input affects the use of research in U.S. regulatory impact analyses (RIAs). We examine changes in the research that is cited in RIAs in response to public comments to assess the influence of participation on the use of information for rulemaking. We conduct an in-depth analysis …
A Diffusion Network Event History Estimator
Research on the diffusion of political decisions across jurisdictions typically accounts for units’ influence over each other with (1) observable measures or (2) by inferring latent network ties from past decisions. The former approach assumes that interdependence is static and perfectly captured by the data. The latter mitigates these issues but requires analytical tools that are separate from the main empirical methods for studying diffusion. A…
Comparing Partial Likelihood and Robust Estimation Methods for the Cox Regression Model
The Cox proportional hazards model is ubiquitous in time-to-event studies of political processes. Plausible deviations from correct specification and operationalization caused by problems such as measurement error or omitted variables can produce substantial bias when the Cox model is estimated by conventional partial likelihood maximization (PLM). One alternative is an iteratively reweighted robust (IRR) estimator, which can reduce this bias. Ho…
Linear Models with Outliers: Choosing between Conditional-Mean and Conditional-Median Methods
State politics researchers commonly employ ordinary least squares (OLS) regression or one of its variants to test linear hypotheses. However, OLS is easily influenced by outliers and thus can produce misleading results when the error term distribution has heavy tails. Here we demonstrate that median regression (MR), an alternative to OLS that conditions the median of the dependent variable (rather than the mean) on the independent variables, can …
Science Use in Regulatory Impact Analysis: The Effects of Political Attention and Controversy
Scholars, policy makers, and research sponsors have long sought to understand the conditions under which scientific research is used in the policy-making process. Recent research has identified a resource that can be used to trace the use of science across time and many policy domains. U.S. federal agencies are mandated by executive order to justify all economically significant regulations by regulatory impact analyses (RIAs), in which they prese…
Considering Network Effects in the Design and Analysis of Field Experiments on State Legislatures
Recent work on legislative politics has documented complex patterns of interaction and collaboration through the lens of network analysis. In a largely separate vein of research, the field experiment—with many applications in state legislatures—has emerged as an important approach in establishing causal identification in the study of legislative politics. The stable unit treatment value assumption (SUTVA)—the assumption that a unit's outcome is u…
Lessons in disguise: Multivariate predictive mistakes in collective choice models
A double-edged sword: The conditional properties of elite network ties in the financial sector
Existing scholarship suggests a deep relationship between elite connections and policy making in the financial sector. But are elite ties between private industry and government a resource for private industry, or a liability? We find that they can be either, depending on the circumstances. We analyze the associations of elite ties within numerous policy-making processes in the financial sector by measuring the network closeness between firms and…
Linear Models with Outliers: Choosing between Conditional-Mean and Conditional-Median Methods
State politics researchers commonly employ ordinary least squares (OLS) regression or one of its variants to test linear hypotheses. However, OLS is easily influenced by outliers and thus can produce misleading results when the error term distribution has heavy tails. Here we demonstrate that median regression (MR), an alternative to OLS that conditions the median of the dependent variable (rather than the mean) on the independent variables, can …
Inferential Network Analysis with Exponential Random Graph Models
Methods for descriptive network analysis have reached statistical maturity and general acceptance across the social sciences in recent years. However, methods for statistical inference with network data remain fledgling by comparison. We introduce and evaluate a general model for inference with network data, the Exponential Random Graph Model (ERGM) and several of its recent extensions. The ERGM simultaneously allows both inference on covariates …
Complex Dependencies in the Alliance Network
The multifaceted and strategic interactions inherent in the formation of international military pacts render the alliance decisions of states highly interdependent. Our aim here is to model the network of alliances in such a way as to capture the effects of covariates and account for the complex dependencies inherent in the network. Regression analysis, due to its foundational assumption of conditional independence, cannot be used to analyze alli…
Toward a Network Theory of Alliance Formation
We propose a network-based theory of alliance formation. Our theory implies that, in addition to key state and dyad attributes already established in the literature, the evolution of the alliance network from any given point in time is largely determined by its structure. Specifically, we argue that closed triangles in the alliance network—where i is allied with j is allied with k is allied with i — produce synergy effects in which state-level ut…
Lessons in disguise: Multivariate predictive mistakes in collective choice models
Comparing Partial Likelihood and Robust Estimation Methods for the Cox Regression Model
The Cox proportional hazards model is ubiquitous in time-to-event studies of political processes. Plausible deviations from correct specification and operationalization caused by problems such as measurement error or omitted variables can produce substantial bias when the Cox model is estimated by conventional partial likelihood maximization (PLM). One alternative is an iteratively reweighted robust (IRR) estimator, which can reduce this bias. Ho…
Micro‐Level Interpretation of Exponential Random Graph Models with Application to Estuary Networks
The exponential random graph model (ERGM) is an increasingly popular method for the statistical analysis of networks that can be used to flexibly analyze the processes by which policy actors organize into a network. Often times, interpretation of ERGM results is conducted at the network level, such that effects are related to overall frequencies of network structures (e.g., the number of closed triangles in a network). This limits the utility of …
Reciprocity and the structural determinants of the international sanctions network
Measuring legislative collaboration: The Senate press events network
Public policy's bibliography: The use of research in US regulatory impact analyses
Major US federal regulatory decisions are developed and justified using regulatory impact analyses (RIAs) mandated by executive order. We examine the scientific citation activity in RIAs, a unique effort that we believe holds significant potential for understanding the use of science in policymaking. This paper reports preliminary findings from collecting and examining scientific citations in 104 RIAs from 2008–2012. We present evidence indicatin…
The Fates of Challengers in U.S. House Elections: The Role of Extended Party Networks in Supporting Candidates and Shaping Electoral Outcomes
Extended party network (EPN) theory characterizes political parties in the United States as dynamic networks of interest groups that collaboratively support favored candidates for office. Electoral predictions derived from EPN theory have yet to be tested on a large sample of races. We operationalize EPNs in the context of organized interest contributions to U.S. House campaigns. We deduce that support by a partisan community of interests signals…
Persistent Policy Pathways: Inferring Diffusion Networks in the American States
The transmission of ideas, information, and resources forms the core of many issues studied in political science, including collective action, cooperation, and development. While these processes imply dynamic connections among political actors, researchers often cannot observe such interdependence. One example is public policy diffusion, which has long been a focus of multiple subfields. In the American state politics context, diffusion is common…
A Critique of Dyadic Design
Dyadic research designs concern data that comprise interactions among actors. They are, without a doubt, the most frequent designs employed in the empirical analysis of international politics. But what do such designs carry with them in terms of theoretical claims and statistical problems? These two issues closely intertwine. When testing hypotheses empirically, the statistical model must be a careful operationalization of the theory under consid…
Science Use in Regulatory Impact Analysis: The Effects of Political Attention and Controversy
Scholars, policy makers, and research sponsors have long sought to understand the conditions under which scientific research is used in the policy-making process. Recent research has identified a resource that can be used to trace the use of science across time and many policy domains. U.S. federal agencies are mandated by executive order to justify all economically significant regulations by regulatory impact analyses (RIAs), in which they prese…
Stochastic weighted graphs: Flexible model specification and simulation
What Can We Learn from Predictive Modeling
The large majority of inferences drawn in empirical political research follow from model-based associations (e.g., regression). Here, we articulate the benefits of predictive modeling as a complement to this approach. Predictive models aim to specify a probabilistic model that provides a good fit to testing data that were not used to estimate the model’s parameters. Our goals are threefold. First, we review the central benefits of this under-util…
Temporal Exponential Random Graph Models with btergm: Estimation and Bootstrap Confidence Intervals
The xergm package is an implementation of extensions to the exponential random graph model (ERGM). It acts as a meta-package for multiple constituent packages. One of these packages is btergm, which implements bootstrap methods for the temporal ERGM estimated by maximum pseudolikelihood. Here, we illustrate the temporal exponential random graph model and its implementation in the package btergm using data on international alliances and a longitud…
Models, methods and network topology: Experimental design for the study of interference
Public Comments’ Influence on Science Use in U.S. Rulemaking: The Case of EPA’s National Emission Standards
Scholarship on bureaucratic policymaking has long focused on both the use of expertise and public accountability. However, few have considered the degree to which public input affects the use of research in U.S. regulatory impact analyses (RIAs). We examine changes in the research that is cited in RIAs in response to public comments to assess the influence of participation on the use of information for rulemaking. We conduct an in-depth analysis …
Speaking truth in power: Scientific evidence as motivation for policy activism
Unelected administrative policymakers rely on the domain expertise and technical integrity of scientific information to maintain perceptions of legitimacy. The necessity that regulatory policymakers rely on sound scientific evidence has been formalized at the US federal level through executive order. Yet, the practical impact of scientific evidence on public support and mobilization for policies remains unclear. We investigate whether individual …
Considering Network Effects in the Design and Analysis of Field Experiments on State Legislatures
Recent work on legislative politics has documented complex patterns of interaction and collaboration through the lens of network analysis. In a largely separate vein of research, the field experiment—with many applications in state legislatures—has emerged as an important approach in establishing causal identification in the study of legislative politics. The stable unit treatment value assumption (SUTVA)—the assumption that a unit's outcome is u…
The contagion of democracy through international networks
Attention to the Covid‐19 Pandemic on Twitter: Partisan Differences Among U.S. State Legislators
Subnational governments in the United States have taken the lead on many aspects of the response to the COVID‐19 pandemic. Variation in government activity across states offers the opportunity to analyze responses in comparable settings. We study a common and informative activity among state officials—state legislators’ attention to the pandemic on Twitter. We find that legislators’ attention to the pandemic strongly correlates with the number of…
Official yet questionable: Examining misinformation in U.S. state legislators’ tweets
We study the roles of elected officials in the dissemination of misinformation on Twitter. This is a particularly salient online population since elected officials serve as primary sources of information for many stakeholders in the public, media, government, and industry. We analyze the content of tweets posted from the accounts of over 3,000 U.S. state lawmakers throughout 2020 and 2021. Specifically, we identify the dissemination of URLs linke…
A Diffusion Network Event History Estimator
Research on the diffusion of political decisions across jurisdictions typically accounts for units’ influence over each other with (1) observable measures or (2) by inferring latent network ties from past decisions. The former approach assumes that interdependence is static and perfectly captured by the data. The latter mitigates these issues but requires analytical tools that are separate from the main empirical methods for studying diffusion. A…
Computer Science (17 works) · Political science (16 works) · Law (15 works) · Economics (14 works) · Politics (14 works) · Electoral Systems and Political Participation (13 works) · Mathematics (13 works) · Statistics (11 works) · Econometrics (10 works) · Law (10 works)