This study shows that political parties have a major impact on the flow of money in extended campaign finance networks that include partisan actors that possess no formal ties to traditional party committees. Using social network analysis and nonparametric statistical techniques, we demonstrate that the strategic objectives and organizational assets of different types of actors heavily influence their network position, activities, and influence. Party committees dominate the networks, but organizations affiliated with congressional leaders and candidates and PACs sponsored by allied interest groups assume important roles in the financing of elections. Our results have implications for party organizational development, interest group behavior, party influence in the legislative process, and the polarization of American politics.
Parties, candidates, and voters are becoming increasingly engaged in political conversations through the micro-blogging platform Twitter. In this paper I show that the structure of the social networks in which they are embedded has the poten- tial to become a source of information about policy positions. Under the assumption that social networks are homophilic (McPherson et al., 2001), this is, the propensity of users to cluster along partisan lines, I develop a Bayesian Spatial Following model that scales Twitter users along a common ideological dimension based on who they follow. I apply this network-based method to estimate ideal points for Twitter users in the US, the UK, Spain, Italy, and the Netherlands. The resulting positions of the party accounts on Twitter are highly correlated with offline measures based on their voting records and their manifestos. Similarly, this method is able to successfully classify individuals who state their political orientation publicly, and a sample of users from the state of Ohio whose Twitter accounts are matched with their voter registration history. To illustrate the potential contribution of these estimates, I examine the extent to which online behavior is polarized along ideological lines. Us- ing the 2012 US presidential election campaign as a case study, I find that public exchanges on Twitter take place predominantly among users with similar viewpoints.
This paper reconsiders Senate action on the 1957 Civil Rights Act, employing a network model of legislative behavior. The Congress possessed a long history of deep divisions over issues related to civil rights for African Americans. Indeed, the 1957 Act became the first major civil rights legislation adopted by the Congress since the end of Southern Reconstruction more than 80 years earlier. Why and how a civil rights bill managed to pass the Senate provides insight regarding both the dynamics of the American party system, as well as the processes by which legislative progress can be achieved in the face of seemingly intractable polarization. We argue that the key to legislative success, as well as to the influence of individual legislators, is directly related to the centrality of particular senators within particular voting blocks, located within networks of relationships that make legislative progress possible. Hence the influence of individual members is not simply due to their ability to cast pivotal votes, but also to their strategic capacity to construct networks of support for legislative initiatives, as well as to their centrality relative to networks of interest and communication within the chamber. Our argument is based on the analysis of several crucial votes during Senate consideration of this landmark civil rights legislation.
The possibility of Iran developing a nuclear weapon is viewed as one of the greatest threats to global security. Iran’s nuclear program receives material, equipment, technology and expertise from suppliers around the world. Halting Iran’s efforts to develop nuclear weapons depends on tracking countries, organizations, and individuals that supply nuclear capabilities to Iran. In this study we employ dynamic social network analysis to map out the suppliers of nuclear capabilities to Iran and their contacts inside Iran as a network that evolves over time. To achieve this end, first, we create a comprehensive dataset that captures nuclear technology, material and knowledge that were supplied to Iran from 1985 to 2012. The primary data sources are the Wisconsin Project on Nuclear Arms Control’s “Iran Watch” dataset (Iran Watch, 2011), IAEA reports assessing Iran’s nuclear posture (e.g. IAEA, 2012); and the Nuclear Threat Initiative (NTI) publication on Nuclear Iran (NTI, 2011). We then process the dataset with the ORA program to elicit the Iran’s nuclear trade network. We employ centrality measures to assess the most influential members of the network (Freeman, 1978). Particular attention is paid to the ‘opinion leaders’ (nodes that have the highest out-degree centrality). Next, we evaluate the critical members of the network based on the type of material or expertise that they supply. Considering that two stages of nuclear capability cycle – Enrichment and Weaponization – specifically contribute to the development of nuclear weapons, we focus on the members of the network that are most central to empowering the weaponization of Iran’s nuclear program. Determining Iran’s most critical suppliers provides necessary insights for any policy directed at disrupting its nuclear capability.
Although the benefits of networking among local governments are well described, and the mechanisms through which inter-governmental relationships work are often studied, the first step in interlocal cooperation is usually overlooked. Cities make interlocal agreements within a network context, but this network and its origins are mostly ignored. There are several possible origins for this network, including similarity of the jurisdictions and shared intergovernmental institutions. The repeated interactions of mayors within these institutions can also drive networking. Institutions which encourage personal interactions in turn improve networking. A survey of Kentucky mayors’ networking is used to test this theory, and while it finds that repeated interactions are a major driver of networking, shared institutions which do not have such interactions also encourage networking. The implications for the understanding of local government networks and for policy are then discussed.
Although patronage politics in democracies has been studied extensively, it is less understood in undemocratic regimes, where a large proportion of the world's population resides. To fill this gap, our paper studies how government officials in authoritarian Vietnam direct public resources toward their hometowns. We manually collect an exhaustive panel dataset of political promotions of officials from 2000 to 2010 and estimate their impact on public infrastructure in their rural hometowns. We obtain three main results. First, promotions of officials improve a wide range of infrastructure in their hometowns, including roads, markets, schools, radio stations, clean water and irrigation. This favoritism is pervasive among officials across different ranks, even among those without budget authority, suggesting informal channels of influence. Second, in contrast to pork-barrel politics in democratic parliaments, elected legislators have no power to exercise favoritism. Third, only home communes receive favors, while larger and more politically important home districts do not. This suggests that favoritism is likely motivated by officials’ social preferences for their hometowns rather than by political considerations.
Social movements rely in large measure on networked communication technologies to organize and disseminate information relating to the movements’ objectives. In this work we seek to understand how the goals and needs of a protest movement are reflected in the geographic patterns of its communication network, and how these patterns differ from those of stable political communication. To this end, we examine an online communication network reconstructed from over 600,000 tweets from a thirty-six week period covering the birth and maturation of the American anticapitalist movement, Occupy Wall Street. We find that, compared to a network of stable domestic political communication, the Occupy Wall Street network exhibits higher levels of locality and a hub and spoke structure, in which the majority of non-local attention is allocated to high-profile locations such as New York, California, and Washington D.C. Moreover, we observe that information flows across state boundaries are more likely to contain framing language and references to the media, while communication among individuals in the same state is more likely to reference protest action and specific places and times. Tying these results to social movement theory, we propose that these features reflect the movement’s efforts to mobilize resources at the local level and to develop narrative frames that reinforce collective purpose at the national level.
Since 1990s when e-government concept was offered various possible models of interactive services have been suggested both by practitioners and theorists all over the world. But the key challenge has been the same - how to find the effective way of citizens engagement using the digital government platform?
The ultimate goal of any e-government project is promotion of transparency and participation. But the paradox of the concept is a traditional one way mechanism of its realization. In fact, all efforts to further the idea in its various forms all over the world are driven by standard top-down administrative commands or directives practically without any input from the civil society itself. Many projects, theoretically intended to be successful, failed basically because of a lack of interest from citizens themselves even despite the fact that huge financial resources were invested for their realization.
In this respect, the recent financial and economic slowdown makes many governments to rethink the whole model and seek not only a more cost-effective, but also a more sustainable way to promote e-government. In this respect, citizen-sourcing concept may address the challenge.
In fact, with minimum of investments and harnessing the collective knowledge of the local society the open data projects are resorting to, the local communities will be able to change the traditional political communication channels between governments and citizens.
We employ social network data from 25 randomly sampled voluntary associations to understand the factors associated with accurate perceptions of the political preferences of fellow group members. We build upon research in communication, social psychology, and social networks to identify relevant predictors. We analyze relationships at the dyadic level, but we also consider the aggregated accuracy of perceptions by ego of alters (“perceptiveness”) and the aggregated accuracy of perception by alters of ego (“explicitness”) regarding political candidate preferences using a multilevel modeling approach. We find relatively low levels of accuracy on average, and in general the variables that predict perceptiveness are not the same variables that predict explicitness. However, there is a consistent and strong link between the frequency of communication (viewed as an indicator of network tie strength) and accuracy both at the dyadic and aggregate levels. However, this relationship is highly contingent on the homophily of political preferences within the group.
This paper employs a small group experiment to study the process of political influence within social networks. Each experimental session involves seven individuals, where privately obtained information is costly but communication within the group is free. Hence, individuals form prior judgments regarding candidates based on public and private information before updating their priors through a process of social communication. In general, individuals select expert informants with political preferences similar to their own, and we consider the dynamic implications for individual and group preferences. In particular, we address the diffusion of information based on a DeGroot model which provides a dynamic formulation of the influence process. We are particularly interested in the implications that arise due to varying levels of information among participants for (1) the construction of communication networks, (2) the relative influence of better informed individuals; (3) relative levels of reliance on priors and communicated messages; (4) the consequences of memory decay for the influence of experts; and (5) the diffusion of information and patterns of persuasion.