Dataset Information

The Multiplex Network of EU Lobby Organizations.

ABSTRACT: The practice of lobbying in the interest of economic or social groups plays an important role in the policy making process of most economies. While no data is available at this stage to examine the success of lobbies in exerting influence on specific policy issues, we perform a first systematic multi-layer network analysis of a large lobby registry. Here we focus on the domains of finance and climate and we combine information on affiliation and client relations from the EU transparency register with information about shareholding and interlocking directorates of firms. We find that the network centrality of lobby organizations has no simple relation with their lobbying budget. Moreover, different layers of the multiplex network provide complementary information to characterize organizations' potential influence. At the aggregate level, it appears that while the domains of finance and climate are separated on the layer of affiliation relations, they become intertwined when economic relations are considered. Because groups of interest differ not only in their budget and network centrality but also in terms of their internal cohesiveness, drawing a map of both connections across and within groups is a precondition to better understand the dynamics of influence on policy making and the forces at play.

SUBMITTER: Zeng A

PROVIDER: S-EPMC5085054 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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The Multiplex Network of EU Lobby Organizations.

Zeng An A Battiston Stefano S

PloS one 20161028 10

The practice of lobbying in the interest of economic or social groups plays an important role in the policy making process of most economies. While no data is available at this stage to examine the success of lobbies in exerting influence on specific policy issues, we perform a first systematic multi-layer network analysis of a large lobby registry. Here we focus on the domains of finance and climate and we combine information on affiliation and client relations from the EU transparency register ...[more]

PMID: 27792734

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Project description:Extensive interdisciplinary literatures have built on the seminal spatial dilemmas model, which depicts the evolution of cooperation on regular lattices, with strategies propagating locally by relative fitness. In this model agents may cooperate with neighbors, paying an individual cost to enhance their collective welfare, or they may exploit cooperative neighbors and diminish collective welfare. Recent research has extended the model in numerous ways, incorporating behavioral noise, implementing other network topologies or adaptive networks, and employing alternative dynamics of replication. Although the underlying dilemma arises from two distinct dimensions-the gains for exploiting cooperative partners (Greed) and the cost of cooperating with exploitative partners (Fear)-most work following from the spatial dilemmas model has argued or assumed that the dilemma can be represented with a single parameter: This research has typically examined Greed or Fear in isolation, or a composite such as the K-index of Cooperation or the ratio of the benefit to cost of cooperation. We challenge this claim on theoretical grounds-showing that embedding interaction in networks generally leads Greed and Fear to have divergent, interactive, and highly nonlinear effects on cooperation at the macro level, even when individuals respond identically to Greed and Fear. Using computational experiments, we characterize both dynamic local behavior and long run outcomes across regions of this space. We also simulate interventions to investigate changes of Greed and Fear over time, showing how model behavior changes asymmetrically as boundaries in payoff space are crossed, leading some interventions to have irreversible effects on cooperation. We then replicate our experiments on inter-organizational network data derived from links through shared directors among 2,400 large US corporations, thus demonstrating our findings for Greed and Fear on a naturally-occurring network. In closing, we discuss implications of our main findings regarding Greed and Fear for the problem of cooperation on inter-organizational networks.

Project description:In the field of deep learning, the processing of large network models on billions or even tens of billions of nodes and numerous edge types is still flawed, and the accuracy of recommendations is greatly compromised when large network embeddings are applied to recommendation systems. To solve the problem of inaccurate recommendations caused by processing deficiencies in large networks, this paper combines the attributed multiplex heterogeneous network with the attention mechanism that introduces the softsign and sigmoid function characteristics and derives a new framework SSN_GATNE-T (S represents the softsign function, SN represents the attention mechanism introduced by the Softsign function, and GATNE-T represents the transductive embeddings learning for attribute multiple heterogeneous networks). The attributed multiplex heterogeneous network can help obtain more user-item information with more attributes. No matter how many nodes and types are included in the model, our model can handle it well, and the improved attention mechanism can help annotations to obtain more useful information via a combination of the two. This can help to mine more potential information to improve the recommendation effect; in addition, the application of the softsign function in the fully connected layer of the model can better reduce the loss of potential user information, which can be used for accurate recommendation by the model. Using the Adam optimizer to optimize the model can not only make our model converge faster, but it is also very helpful for model tuning. The proposed framework SSN_GATNE-T was tested for two different types of datasets, Amazon and YouTube, using three evaluation indices, ROC-AUC (receiver operating characteristic-area under curve), PR-AUC (precision recall-area under curve) and F1 (F1-score), and found that SSN_GATNE-T improved on all three evaluation indices compared to the mainstream recommendation models currently in existence. This not only demonstrates that the framework can deal well with the shortcomings of obtaining accurate interaction information due to the presence of a large number of nodes and edge types of the embedding of large network models, but also demonstrates the effectiveness of addressing the shortcomings of large networks to improve recommendation performance. In addition, the model is also a good solution to the cold start problem.

Project description:BackgroundThe global tobacco epidemic claims 5 million lives each year, facilitated by the ability of transnational tobacco companies to delay or thwart meaningful tobacco control worldwide. A series of cross-company tobacco industry "issues management organizations" has played an important role in coordinating and implementing common strategies to defeat tobacco control efforts at international, national, and regional levels. This study examines the development and enumerates the activities of these organizations and explores the implications of continuing industry cooperation for global public health.MethodsUsing a snowball sampling strategy, we collected documentary data from tobacco industry documents archives and assembled them into a chronologically organized case study.ResultsThe International Committee on Smoking Issues (ICOSI) was formed in 1977 by seven tobacco company chief executives to create common anti-tobacco control strategies and build a global network of regional and national manufacturing associations. The organization's name subsequently changed to INFOTAB. The multinational companies built the organization rapidly: by 1984, it had 69 members operating in 57 countries. INFOTAB material, including position papers and "action kits" helped members challenge local tobacco control measures and maintain tobacco-friendly environments. In 1992 INFOTAB was replaced by two smaller organizations. The Tobacco Documentation Centre, which continues to operate, distributes smoking-related information and industry argumentation to members, some produced by cross-company committees. Agro-Tobacco Services, and now Hallmark Marketing Services, assists the INFOTAB-backed and industry supported International Tobacco Growers Association in advancing claims regarding the economic importance of tobacco in developing nations.ConclusionThe massive scale and scope of this industry effort illustrate how corporate interests, when threatened by the globalization of public health, sidestep competitive concerns to coordinate their activities. The global network of national and regional manufacturing associations created and nurtured by INFOTAB remains active, particularly in relation to the recently negotiated global health treaty, the Framework Convention on Tobacco Control. Policymakers should be aware that although these associations claim to represent only national or regional interests, they are allied to and coordinated with a confederation of transnational tobacco companies seeking to protect profits by undermining public health.

Dataset Information

The Multiplex Network of EU Lobby Organizations.

Publications

The Multiplex Network of EU Lobby Organizations.

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