Exploring the Political Agenda of the European Parliament Using a Dynamic Topic Modeling Approach
Insight Centre for Data Analytics（洞察数据分析中心）；School of Computer Science, University College Dublin（都柏林大学计算机科学学院）；School of Politics & International Relations, University College Dublin（都柏林大学政治与国际关系学院）
Derek Greene, James P. Cross
备注：
Long version including appendix. arXiv admin note: substantial text overlap with arXiv:1505.07302
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 1999-2014. 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 behaviour and the committee structure of the Parliament.
Federal University of Minas Gerais（米纳斯吉拉斯联邦大学）；State University of Southwestern of Bahia（巴伊亚西南州立大学）；Federal University of Bahia（巴伊亚联邦大学）
Since June 2013, when Brazil faced the largest and most significant mass protests in a generation, a political crisis is in course. In midst of this crisis, Brazilian politicians use social media to communicate with the electorate in order to retain or to grow their political capital. The problem is that many controversial topics are in course and deputies may prefer to avoid such themes in their messages. To characterize this behavior, we propose a method to accurately identify political and non-political tweets independently of the deputy who posted it and of the time it was posted. Moreover…
Supercharging Agenda Setting Research: The ParlaCAP Dataset of 28 European Parliaments and a Scalable Multilingual LLM-Based Classification
Jožef Stefan Institute（焦兹夫·斯蒂芬研究所）；Faculty of Computer and Information Science（计算机与信息科学系）；University of Ljubljana（卢布尔雅那大学）；Institute of Contemporary History（当代历史研究所）；Faculty of Political Science（政治科学系）；University of Zagreb（扎格列布大学）
Stockholm University（斯德哥尔摩大学）；Athens University of Economics & Business（雅典经济与商业大学）
Large, diachronic datasets of political discourse are hard to come across, especially for resource-lean languages such as Greek. In this paper, we introduce a curated dataset of the Greek Parliament Proceedings that extends chronologically from 1989 up to 2020. It consists of more than 1 million speeches with extensive metadata, extracted from 5,355 parliamentary record files. We explain how it was constructed and the challenges that we had to overcome. The dataset can be used for both computational linguistics and political analysis-ideally, combining the two. We present such an application, …
University of Exeter（埃克塞特大学）；Oxford Internet Institute（牛津互联网研究院）；University of Oxford（牛津大学）；King’s College London（伦敦国王学院）；Alan Turing Institute（艾伦·图灵研究所）；Meedan
Recent election surprises, regime changes, and political shocks indicate that political agendas have become more fast-moving and volatile. The ability to measure the complex dynamics of agenda change and capture the nature and extent of volatility in political systems is therefore more crucial than ever before. This study proposes a definition and operationalization of volatility that combines insights from political science, communications, information theory, and computational techniques. The proposed measures of fractionalization and agenda change encompass the shifting salience of issues i…
Multilingual Power and Ideology Identification in the Parliament: a Reference Dataset and Simple Baselines
University of Tübingen（蒂宾根大学）；Charles University（查理大学）；Jožef Stefan Institute（约热夫·斯泰凡研究所）；Kaunas University of Technology（考纳斯理工大学）；Jožef Stefan International Postgraduate School（约热夫·斯泰凡国际研究生院）
Multi-aspect Multilingual and Cross-lingual Parliamentary Speech Analysis
West University of Timisoara（蒂米什瓦拉西部大学）；Universidad de Granada（格拉纳达大学）；Sofia University St. Kl. Ohridski（圣克莱门特奥赫里德斯基索非亚大学）；Institute of Information and Communication Technologies, Bulgarian Academy of Sciences（保加利亚科学院信息与通信技术研究所）；University of Zaragoza（萨拉戈萨大学）；University of Ljubljana（卢布尔雅那大学）
Putnam Science Academy（普特南科学院）；Princeton High School（普林斯顿高中）；Zhengzhou University（郑州大学）；Huazhong University of Science and Technology（华中科技大学）
This study verified the effectiveness of Donald Trump's Twitter campaign in guiding agen-da-setting and deflecting political risk and examined Trump's Twitter communication strategy and explores the communication effects of his tweet content during Covid-19 pandemic. We collected all tweets posted by Trump on the Twitter platform from January 1, 2020 to December 31, 2020.We used Ordinary Least Squares (OLS) regression analysis with a fixed effects model to analyze the existence of the Twitter strategy. The correlation between the number of con-firmed daily Covid-19 diagnoses and the number of …
Carnegie Mellon University（卡内基梅隆大学）；University of Haifa（海法大学）；Stanford University（斯坦福大学）
Amidst growing concern over media manipulation, NLP attention has focused on overt strategies like censorship and "fake news'". Here, we draw on two concepts from the political science literature to explore subtler strategies for government media manipulation: agenda-setting (selecting what topics to cover) and framing (deciding how topics are covered). We analyze 13 years (100K articles) of the Russian newspaper Izvestia and identify a strategy of distraction: articles mention the U.S. more frequently in the month directly following an economic downturn in Russia. We introduce embedding-based…
Jožef Stefan Institute（约瑟夫·斯蒂芬研究所）；Université Panthéon-Sorbonne（巴黎第一大学）；Paris School of Economics（巴黎经济学院）
We study the cohesion within and the coalitions between political groups in the Eighth European Parliament (2014--2019) by analyzing two entirely different aspects of the behavior of the Members of the European Parliament (MEPs) in the policy-making processes. On one hand, we analyze their co-voting patterns and, on the other, their retweeting behavior. We make use of two diverse datasets in the analysis. The first one is the roll-call vote dataset, where cohesion is regarded as the tendency to co-vote within a group, and a coalition is formed when the members of several groups exhibit a high …
Benchmarking Gender and Political Bias in Large Language Models
School of Computing & Information Systems, The University of Melbourne（墨尔本大学计算与信息系统学院）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）
