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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

portfolio

publications

The significance of economy in the Russian bi-lateral treaty process

Published in Communist and Post-Communist Studies, 2005

This paper is about the bi-lateral agreements between the federal center and regions in Russia.

Recommended citation: Dusseault, David, Martin Ejnar Hansen, and Slava Jankin Mikhaylov (2005). "The significance of economy in the Russian bi-lateral treaty process." Communist and Post-Communist Studies 38: 121-130.

Policy Performance and Support for European Integration

Published in The Legitimacy of the European Union After Enlargement, Jacques Thomassen (ed.), Oxford University Press, 2009

This paper is about support for European integration.

Recommended citation: Slava Jankin Mikhaylov and Michael Marsh (2009). "Policy Performance and Support for European Integration." In The Legitimacy of the European Union After Enlargement, Jacques Thomassen (ed.), Oxford University Press.

European Parliament elections and EU governance

Published in Living Reviews in European Governance, 2010

This paper is second-order elections.

Recommended citation: Michael Marsh and Slava Jankin Mikhaylov (2010). "European Parliament elections and EU governance." Living Reviews in European Governance, 5(4).

Scaling Policy Preferences From Coded Political Texts

Published in Legislative Studies Quarterly, 2011

This paper is about scaling models.

Recommended citation: Lowe, Will, Kenneth Benoit, Slava Jankin Mikhaylov, and Michael Laver (2011). "Scaling Policy Preferences From Coded Political Texts." Legislative Studies Quarterly, 36(1, Feb): 123-155.

Natural Sentences as Valid Units for Coded Political Texts

Published in British Journal of Political Science, 2012

This paper is about text units in human coding, and consequences for bias and error.

Recommended citation: Thomas Daubler, Kenneth Benoit, Slava Jankin Mikhaylov, and Michael Laver (2012). "Natural Sentences as Valid Units for Coded Political Texts." British Journal of Political Science, 42(4): 937-951.

Economic voting in a crisis: the Irish election of 2011

Published in Electoral Studies, 2012

This paper is about economic voting in crisis.

Recommended citation: Michael Marsh and Slava Jankin Mikhaylov (2012). "Economic voting in a crisis: the Irish election of 2011." Electoral Studies, 31(3): 478-484.

How to scale coded text units without bias: A response to Gemenis

Published in Electoral Studies, 2012

This paper is about using manifestos for policy position estimates.

Recommended citation: Kenneth Benoit, Michael Laver, Will Lowe, and Slava Jankin Mikhaylov (2012). "How to scale coded text units without bias: A response to Gemenis." Electoral Studies, 31(3): 605-608.

Born to Lead? A Twin Design and Genetic Association Study of Leadership Role Occupancy

Published in The Leadership Quarterly, 2013

This paper is about genetics of leadership.

Recommended citation: Jan-Emmanuel De Neve, Slava Jankin Mikhaylov, Christopher T. Dawes, Nicholas A. Christakis, James H. Fowler (2013). "Born to Lead? A Twin Design and Genetic Association Study of Leadership Role Occupancy." The Leadership Quarterly, 24(1): 45-60.

A Conservative Revolution: The electoral response to economic crisis in Ireland

Published in Journal of Elections, Public Opinion and Parties, 2014

This paper is about electoral results in Ireland.

Recommended citation: Michael Marsh and Slava Jankin Mikhaylov (2014). "A Conservative Revolution: The electoral response to economic crisis in Ireland." Journal of Elections, Public Opinion and Parties, 24(2): 160-179.

Crowd-Sourced Text Analysis: Reproducible and agile production of political data

Published in American Political Science Review, 2016

This paper is about crowdsourcing core political science data.

Recommended citation: Kenneth Benoit, Drew Conway, Benjamin E. Lauderdale, Michael Laver, and Slava Jankin Mikhaylov (2016). "Crowd-Sourced Text Analysis: Reproducible and agile production of political data." American Political Science Review, 110(2): 278-295.

Database of Parliamentary Speeches in Ireland, 1919-2013

Published in IEEE Proceedings of the 2017 International Conference on the Frontiers and Advances in Data Science (FADS), 2017

This paper is about Irish parliamentary debates.

Recommended citation: Alexander Herzog and Slava Jankin Mikhaylov (2017). "Database of Parliamentary Speeches in Ireland, 1919-2013." IEEE Proceedings of the 2017 International Conference on the Frontiers and Advances in Data Science (FADS), 23-25 October 2017, Xi’an, China: 29-34.

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

Published in IEEE Proceedings of the 2017 International Conference on the Frontiers and Advances in Data Science (FADS), 2017

This paper is about preference dynamics in UN General Debates.

Recommended citation: Stefano Gurciullo and Slava Jankin Mikhaylov (2017). "Detecting Policy Preferences and Dynamics in the UN General Debate with Neural Word Embeddings." IEEE Proceedings of the 2017 International Conference on the Frontiers and Advances in Data Science (FADS), 23-25 October 2017, Xi’an, China: 74-79.

Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration

Published in Philosophical Transactions of the Royal Society A, 2018

This paper is about AI and cross-sectoral collaboration.

Recommended citation: Slava Jankin Mikhaylov, Marc Esteve, and Averill Campion (2018). "Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration." Philosophical Transactions of the Royal Society A, Volume 376, Issue 2128.

talks

Data science for the public sector

Published:

Public sector organisations are increasingly interested in using data science capabilities to deliver policy and generate efficiencies in high uncertainty environments. The long-term success of data science in the public sector relies on successfully embedding it into delivery solutions for policy implementation. This requires organisational innovation and change delivered through structural and cultural adaptation, together with capacity building. Another key factor for success is the contribution of academia and the private and third sector. This talk will discuss the opportunities that exist for using data science in delivering public services at the international and national levels.

Text Analysis and International Organizations

Published:

This tutorial covers how diplomats can use data and sophisticated analytical tools (namely Natural Language Processing and advanced statistical methods) to better understand and conduct multilateral diplomacy.

Transfer Topic Labeling with Domain-Specific Knowledge Base: An Analysis of UK House of Commons Speeches 1935-2014

Published:

Topic models are widely used in natural language processing, allowing researchers to estimate the underlying themes in a collection of documents. Most topic models use unsupervised methods and hence require the additional step of attaching meaningful labels to estimated topics. This process of manual labeling is not scalable and suffers from human bias. We present a transfer learning approach to topic labeling that leverages existing knowledge-base in political science to automatically label topics. These labels can be used instead of human labeling or supplementing it by guiding the labeling process in a more replicable procedure by retaining humans in the loop. We demonstrate our approach with a large scale topic model analysis of the complete corpus of UK House of Commons speeches 1935-2014, using the coding instructions of the Comparative Agendas Project to label topics. We evaluate our results using human expert coding. We show that our approach works well for a majority of the topics we estimate; but we also find that institution-specific topics, in particular on subnational governance, require manual input.

Data Science and AI for Public Good: Lessons from cross-sectoral collaboration

Published:

Around the world, cross-sectoral collaborations between universities and the public sector are the norm for leveraging data science and artificial intelligence based capabilities to deliver policy and shape efficiencies in highly uncertain environments. In line with this vision, the HEFCE funded Catalyst Project brought together Essex County Council, Suffolk County Council, and University of Essex to enable innovative and far reaching responses to pressing national and local issues. While such cross-sectoral collaboration is not new, there is a lack of a systematic review of the empirical evidence about which managerial strategies help overcome the serious challenges involved with interorganisational collaboration. This talk presents the first results from a programme of study to take stock of the lessons learnt in the project around collaboration between public authorities and the University and to place these in the context of global best practices in cross-sectoral collaboration.

NLP Applications in Political Science

Published:

Political science scholars working with large quantities of textual data are often interested in discovering latent semantic structures in their document collections. Examples include legislative debates, policies, media content, manifestos, and open-ended survey questions. Domain idiosyncrasies often do not allow direct application of standard NLP toolkit. This talk will introduce several recent applications in the areas of climate change politics, international relations, legislative politics, and armed conflict prediction.

teaching

Introduction to Data Science and Big Data Analytics

Summer School, London School of Economics, 2018

This course integrates prior training in quantitative methods (statistics) and coding with substantive expertise and introduces the fundamental concepts and techniques of Data Science and Big Data Analytics. Typical students will be advanced undergraduate and postgraduate students from any field requiring the fundamentals of data science or working with typically large datasets and databases. Practitioners from industry, government, or research organisations with some basic training in quantitative analysis or computer programming are also welcome. Because this course surveys diverse techniques and methods, it makes an ideal foundation for more advanced or more specific training. Our applications are drawn from social, political, economic, legal, and business and marketing fields.

Applied Machine Learning

MSc, Hertie School of Governance, 2019

Data Science is an exciting new area that combines scientific inquiry, substantive expertise, programming, and statistical knowledge. One of the main challenges for businesses and policy makers when integrating data science is to find people with the appropriate skills. Data science is no longer only the domain of computer scientists and engineers. Good data science requires experts that combine substantive knowledge with data analytical skills, which makes it a prime area for social scientists with an interest in cutting-edge research. A key technology in data science is machine learning.

Natural Language Processing

MSc, Hertie School of Governance, 2019

Natural Language Processing (NLP) is a key technology of the information age. Understanding language is also a crucial part of artificial intelligence. Applications of NLP are everywhere because people and institutions largely communicate in language. We encounter NLP every day from web search, emails and customer service to party manifestos and automation of legal and public services. We also observe NLP used to weaponize social media for electoral interference. There are a large variety of underlying machine learning models behind NLP applications.