Networks among legislators shape politics and policymaking within legislative institutions. In past work on legislative networks, the ties between legislators have been defined on those who serve in the same legislature or chamber. Online information networks, which have been found to play important roles in legislative communication at the national level, are not bounded by individual legislative bodies. We collect original data for over four thousand US state legislators and study patterns of connection among them on Twitter. We look at three types of Twitter networks—follower, retweets, and mentions. We describe these networks and estimate the relationships between ties and salient attributes of legislators. We find that networks are organized largely along geographic and partisan lines and that identity attributes—namely gender and race—exhibit strong associations with the formation of ties.

Legislative staffers are an invisible force in legislative bodies that provide every imaginable service. It is doubtful that modern legislatures could operate without them. Prior studies of Congressional staffers have found evidence that staffers not only aid but also exert an independent influence on the policy-making process through network effects. In this article, I test if this extends to state legislative staffers using novel data from shared staffer networks in Arizona, Indiana, and New Mexico. I argue that, compared to their Congressional counterparts, state legislative staffers are more akin to ‘clerks’ than ‘political professionals’ and this limits their ability to independently influence policymaking at the state level.

In 2017, archaeologists at Pompeii discovered by far the longest tomb inscription ever found at the city on a monumental tomb. This elogium provided insight into many aspects of the city's social, economic, and political world. One clause attests to the distribution of baked bread in the city. This note argues that the passage provides new evidence from Pompeii that answers two longstanding questions. The first is that of the subject of an often-reproduced Pompeian fresco. The identity of the main figure in the painting is debated: either a baker or a politician. The second is the status, political rank, and network of the owner of the property on which the fresco was discovered. Supported by the evidence of an electoral programma, the painting and inscription illuminate the mechanics of beneficence at Pompeii and serve to identify the residence of someone who operated in the political networks of the 1st-c. CE city at a sub-elite level.

Undirected, binary network data consist of indicators of symmetric relations between pairs of actors. Regression models of such data allow for the estimation of effects of exogenous covariates on the network and for prediction of unobserved data. Ideally, estimators of the regression parameters should account for the inherent dependencies among relations in the network that involve the same actor. To account for such dependencies, researchers have developed a host of latent variable network models; however, estimation of many latent variable network models is computationally onerous and which model is best to base inference upon may not be clear. We propose the probit exchangeable (PX) model for undirected binary network data that is based on an assumption of exchangeability, which is common to many of the latent variable network models in the literature. The PX model can represent the first two moments of any exchangeable network model. We leverage the EM algorithm to obtain an approximate maximum likelihood estimator of the PX model that is extremely computationally efficient. Using simulation studies, we demonstrate the improvement in estimation of regression coefficients of the proposed model over existing latent variable network models. In an analysis of purchases of politically aligned books, we demonstrate political polarization in purchase behavior and show that the proposed estimator significantly reduces runtime relative to estimators of latent variable network models, while maintaining predictive performance.

We investigate structural features and processes associated with the onset of systemic conflict using an approach which integrates complex systems theory with network modeling and analysis. We present a signed network model of cooperation and conflict dynamics in the context of international relations between states. The model evolves ties between nodes under the influence of a structural balance force and a dyad-specific force. Model simulations exhibit a sharp bifurcation from peace to systemic war as structural balance pressures increase, a bistable regime in which both peace and war stable equilibria exist, and a hysteretic reverse bifurcation from war to peace. We show how the analytical expression we derive for the peace-to-war bifurcation condition implies that polarized network structure increases susceptibility to systemic war. We develop a framework for identifying patterns of relationship perturbations that are most destabilizing and apply it to the network of European great powers before World War I. We also show that the model exhibits critical slowing down, in which perturbations to the peace equilibrium take longer to decay as the system draws closer to the bifurcation. We discuss how our results relate to international relations theories on the causes and catalysts of systemic war.

We present a model of political networks that integrates both the choice of trade partners (the extensive margin) and trade volumes (the intensive margin). Our model predicts that regimes secure in their survival, including democracies as well as some consolidated authoritarian regimes, will trade more on the extensive margin than vulnerable autocracies, which will block trade in products that would expand interpersonal contact among their citizens. We apply a two-stage Bayesian LASSO estimator to detailed measures of institutional features and highly disaggregated product-level trade data encompassing 131 countries over a half century. Consistent with our model, we find that (a) political institutions matter for the extensive margin of trade but not for the intensive margin and (b) the effects of political institutions on the extensive margin of trade vary across products, falling most heavily on those goods that involve extensive interpersonal contact.

Several hundred inscribed bronze objects dating from Western and Eastern Zhou periods were commissioned for or by married women. Several dozen inscriptions are known whose commissioners called themselves sheng 生 (甥) of a number of lineages. In pre-Qin Chinese, the term sheng 甥 designated several categories of affinal relatives: paternal aunts’ sons, maternal uncles’ sons, wives’ brothers, sisters’ husbands, and sons of sisters or daughters. The wide geographical and chronological spread of female- or sheng-related vessels, as well as dedications to “many affinal relatives” (hungou 婚購) in bronze inscriptions point to the importance of marital ties in early Chinese society and politics.

Focusing on the inscriptions commissioned by sheng, the present article suggests that even when concluded at a considerable distance, marriages produced long-term mutual obligations for male members of the participating lineages or principalities. Affinal relationships represented social and political capital that could be converted in terms of individuals’ careers and prestige or benefits for their whole lineages/states. In sum, starting from the early Western Zhou period, marital alliances represented a substantial integrative factor in early Chinese politics. On the one hand, marital alliances helped to consolidate the radial network of Zhou states centered on the Zhou king. On the other hand, they facilitated the construction of decentralized regional and interregional inter-state networks. The latter guaranteed the stability of the Zhou political system even when it had a weak center. As a result, the Zhou networks did not fall apart following crises in the Zhou royal house, but continued to expand by the inclusion of new members.