Detecting Policy Preferences and Dynamics in the UN General Debate with Neural Word Embeddings

Foreign policy analysis has been struggling to find ways to measure policy preferences and paradigm shifts in international political systems. This paper presents a novel, potential solution to this challenge, through the application of a neural word embedding (Word2vec) model on a dataset featuring speeches by heads of state or government in the United Nations General Debate. The paper provides three key contributions based on the output of the Word2vec model. First, it presents a set of policy attention indices, synthesizing the semantic proximity of political speeches to specific policy themes. Second, it introduces country-specific semantic centrality indices, based on topological analyses of countries' semantic positions with respect to each other. Third, it tests the hypothesis that there exists a statistical relation between the semantic content of political speeches and UN voting behavior, falsifying it and suggesting that political speeches contain information of different nature then the one behind voting outcomes. The paper concludes with a discussion of the practical use of its results and consequences for foreign policy analysis, public accountability, and transparency

Topology Analysis of International Networks Based on Debates in the United Nations

In complex, high dimensional and unstructured data it is often difficult to extract meaningful patterns. This is especially the case when dealing with textual data. Recent studies in machine learning, information theory and network science have developed several novel instruments to extract the semantics of unstructured data, and harness it to build a network of relations. Such approaches serve as an efficient tool for dimensionality reduction and pattern detection. This paper applies semantic network science to extract ideological proximity in the international arena, by focusing on the data from General Debates in the UN General Assembly on the topics of high salience to international community. UN General Debate corpus (UNGDC) covers all high-level debates in the UN General Assembly from 1970 to 2014, covering all UN member states. The research proceeds in three main steps. First, Latent Dirichlet Allocation (LDA) is used to extract the topics of the UN speeches, and therefore semantic information. Each country is then assigned a vector specifying the exposure to each of the topics identified. This intermediate output is then used in to construct a network of countries based on information theoretical metrics where the links capture similar vectorial patterns in the topic distributions. Topology of the networks is then analyzed through network properties like density, path length and clustering. Finally, we identify specific topological features of our networks using the map equation framework to detect communities in our networks of countries

Influence in economic and political systems: A network scientific approach

Complex social systems strive by exchanging information and resources. By means of the exchange, some actors in the system are able to at least partially determine the behaviour of another actor, thereby influencing it. Both the information exchange process and the degree of actors’ influence are latent, unobserved phenomena in many instances of real-world systems. This thesis presents a framework that intends to unearth the two hidden properties. It does so by introducing a Network Inference and Influence Framework (NIIF), which makes use of graph-based methods to derive a latent network in a social system, and measure the influence of its elements. The framework is applied on three case studies where the latency problem translates into research questions with importance for public policy making. The first case study uses NIIF to estimate the latent network of interdependency across financial institutions, and measures the extent to which a bank may negatively influence the system after an economic distress. In the second case study, a network of information diffusion is extracted from House of Commons parliamentary debates, testing the relation between the resulted metric of influence and speakers’ positions in government. The last case study builds a network of semantic and ideological affinity across UN General Assembly members, showing how graph-based methods can detect global political change. The thesis concludes with a discussion of potential future usages of the framework, as well as ameliorations

Caractérisation expérimentale des performances d'un propulseur de Hall 50W

International audienceThe performance metrics and the plume characteristics of a miniaturised Hall thruster are investigated. The thruster is part of the ExoMG-nano propulsion platform developed by Exotrail and, during the test campaign, it is operated with a power processing unit prototype. Beam divergence, ion energy distribution, thrust and specic impulse are the primary parameters measured during the investigation. The thrust is directly measured with a pendulum-type thrust balance, while the ion current density and ion energy distribution are measured using electrostatic probes. At about 53W of total input power and at a total xenon flow rate of 2.7 sccm (anode plus cathode), the thrust, total specific impulse and total effciency are 2 mN, 800 s and 15%, respectively. At the same power, the mass utilisation effciency is about 67 %, the divergence effciency is 70-75% and the half-angle where 90% of the plume ion current is found is 68-72o. A comparison with other commercially available propulsion platforms is also presented

Complex Politics: A Quantitative Semantic and Topological Analysis of UK House of Commons Debates

This study is a first, exploratory attempt to use quantitative semantics techniques and topological analysis to analyze systemic patterns arising in a complex political system. In particular, we use a rich data set covering all speeches and debates in the UK House of Commons between 1975 and 2014. By the use of dynamic topic modeling (DTM) and topological data analysis (TDA) we show that both members and parties feature specific roles within the system, consistent over time, and extract global patterns indicating levels of political cohesion. Our results provide a wide array of novel hypotheses about the complex dynamics of political systems, with valuable policy applications