Research Output
1 - 6 of 6
Publication
Unveiling the Political Agenda of the European Parliament Plenary: A Topical Analysis
2015-07-01, Greene, Derek, Cross, James P.
This study analyzes political interactions in the European Parliament (EP) by considering how the political agenda of the plenary sessions has evolved over time and the manner in which Members of the European Parliament (MEPs) have reacted to external and internal stimuli when making Parliamentary speeches. It does so by considering the context in which speeches are made, and the content of those speeches. To detect latent themes in legislative speeches over time, speech content is analyzed using a new dynamic topic modeling method, based on two layers of matrix factorization. This method is applied to a new corpus of all English language legislative speeches in the EP plenary from the period 1999- 2014. Our findings suggest that the political agenda of the EP has evolved significantly over time, is impacted upon by the committee structure of the Parliament, and reacts to exogenous events such as EU Treaty referenda and the emergence of the Euro-crisis have a significant impact on what is being discussed in Parliament.
Publication
Talk is not cheap: Policy agendas, information processing, and the unusually proportional nature of European Central Bank communications policy responses
2020-04, Cross, James P., Greene, Derek
This article unveils the policy agenda of the European Central Bank (ECB) Governing Council as found in the speeches that Governing Council Members gave between 1999 and 2018. Using a dynamic topic‐modeling approached based on non‐negative matrix factorization, we demonstrate how the issues discussed by ECB Governing Council members have evolved over time, and how the general punctuation hypothesis (Jones, B. D. & Baumgartner, F. R. (2005). The politics of attention: How government prioritizes problems. University of Chicago Press) sheds light on what drives this process. We find that unlike policy outputs from many other policymaking systems, ECB communications evolve in a proportional manner. We attribute this finding to the information‐processing capacities of the bank. Our findings speak to the literatures on central bank communications, the evolution of policy agendas, and the application of topic models to speech texts.
Publication
A mathematical model for plasticity and damage: A discrete calculus formulation
2017-03-01, Dassios, Ioannis K., Jivkov, Andrey P., Abu-Muharib, Andrew, James, Peter
In this article we propose a discrete lattice model to simulate the elastic, plastic and failure behaviour of isotropic materials. Focus is given on the mathematical derivation of the lattice elements, nodes and edges, in the presence of plastic deformations and damage, i.e. stiffness degradation. By using discrete calculus and introducing non-local potential for plasticity, a force-based approach, we provide a matrix formulation necessary for software implementation. The output is a non-linear system with allowance for elasticity, plasticity and damage in lattices. This is the key tool for explicit analysis of micro-crack generation and population growth in plastically deforming metals, leading to macroscopic degradation of their mechanical properties and fitness for service. An illustrative example, analysing a local region of a node, is given to demonstrate the system performance.
Publication
Dimensionality Reduction and Visualisation Tools for Voting Record
2016-09-21, Brigadir, Igor, Greene, Derek, Cross, James P., Cunningham, Pádraig
Recorded votes in legislative bodies are an important source of data for political scientists. Voting records can be used to describe parliamentary processes, identify ideological divides between members and reveal the strength of party cohesion. We explore the problem of working with vote data using popular dimensionality reduction techniques and cluster validation methods, as an alternative to more traditional scaling techniques. We present results of dimensionality reduction techniques applied to votes from the 6th and 7th European Parliaments, covering activity from 2004 to 2014.
Publication
Exploring the Political Agenda of the European Parliament Using a Dynamic Topic Modeling Approach
2017-01, Greene, Derek, Cross, James P.
This study analyzes the political agenda of the European Parliament (EP) plenary, how it has evolved over time, and the manner in which Members of the European Parliament (MEPs) have reacted to external and internal stimuli when making plenary speeches. To unveil the plenary agenda and detect latent themes in legislative speeches over time, MEP speech content is analyzed using a new dynamic topic modeling method based on two layers of Non-negative Matrix Factorization (NMF). This method is applied to a new corpus of all English language legislative speeches in the EP plenary from the period 1999 to 2014. Our findings suggest that two-layer NMF is a valuable alternative to existing dynamic topic modeling approaches found in the literature, and can unveil niche topics and associated vocabularies not captured by existing methods. Substantively, our findings suggest that the political agenda of the EP evolves significantly over time and reacts to exogenous events such as EU Treaty referenda and the emergence of the Euro Crisis. MEP contributions to the plenary agenda are also found to be impacted upon by voting behavior and the committee structure of the Parliament.
Publication
Tweeting Europe: A text-analytic approach to unveiling the content of political actors' Twitter activities in the European Parliament
2016-06-25, Cross, James P., Greene, Derek, Belford, Mark
Twitter is an important platform for communication and is frequently used by Members of the European Parliament (MEPs) to campaign and en- gage in discussion with constituents and colleagues in the parliament. Ex- amining the issues that MEPs talk about on Twitter can thus inform us about their political priorities. Topic modelling aims to summarise a corpus of documents by capturing the underlying hidden structure of the data and pre- senting the user with an overview of the key subjects and themes discussed in the corpus, known as topics. This paper aims to quantify and explore the content that MEPs pay attention to on Twitter by applying a new en- semble approach for topic modelling which involves applying two layers of Non-Negative Matrix Factorisation (NMF). The resulting set of issues paid attention to by MEPs are explained by considering the effects of events, is- sue characteristics, and MEP characteristics.