Predicting vote choice in the 2020 Irish general election

Elkink, Johan A.; Farrell, David M.

doi:10.1080/07907184.2021.1978219

Cited by 16 publications

(6 citation statements)

References 19 publications

(9 reference statements)

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“…Rudkowsky et al [51] study several machine learning approaches based on word embeddings for Austrian parliamentary speeches. Similarly, Abercrombie and Batista-Navarro [1] and Elkink and Farrell [18] investigate predicting votes based on the parliament speeches.…”

Section: Sentiment In Politicsmentioning

confidence: 99%

Multi-aspect multilingual and cross-lingual parliamentary speech analysis

Miok,

Hidalgo Tenorio,

Osenova

et al. 2024

IDA

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Parliamentary and legislative debate transcripts provide an informative insight into elected politicians’ opinions, positions, and policy preferences. They are interesting for political and social sciences as well as linguistics and natural language processing (NLP) research. While exiting research studied individual parliaments, we apply advanced NLP methods to a joint and comparative analysis of six national parliaments (Bulgarian, Czech, French, Slovene, Spanish, and United Kingdom) between 2017 and 2020. We analyze emotions and sentiment in the transcripts from the ParlaMint dataset collection, and assess if the age, gender, and political orientation of speakers can be detected from their speeches. The results show some commonalities and many surprising differences among the analyzed countries.

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Section: Sentiment In Politicsmentioning

confidence: 99%

Multi-aspect multilingual and cross-lingual parliamentary speech analysis

Miok,

Hidalgo Tenorio,

Osenova

et al. 2024

IDA

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“…It resulted in Fine Gael and Fianna Fáil forming an unprecedented coalition with rotation of the Taoiseach's office. This election outcome led Field (2020) to conclude that Ireland was a 'two-and-a-half party system no more' and Elkink and Farrell (2021) (Power, 2016;Power and Nussbaum, 2016). Layte and Landy (2018) argue the continued delivery of basic services and welfare (unlike in Greece) prevented the emergence of unrest in the immediate aftermath of the financial crash.…”

Section: Ireland Political and Social Dynamicsmentioning

confidence: 99%

Changing social and political attitudes in Ireland and Northern Ireland

Laurence,

Sprong,

McGinnity

et al. 2023

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The mission of the Economic and Social Research Institute (ESRI) is to advance evidence based policymaking that supports economic sustainability and social progress in Ireland. ESRI researchers apply the highest standards of academic excellence to challenges facing policymakers, focusing on 10 areas of critical importance to 21st Century Ireland.The Institute was founded in 1960 by a group of senior civil servants led by Dr T.K. Whitaker, who identified the need for independent and in-depth research analysis to provide a robust evidence base for policymaking in Ireland.Since then, the Institute has remained committed to independent research and its work is free of any expressed ideology or political position. The Institute publishes all research reaching the appropriate academic standard, irrespective of its findings or who funds the research.The quality of its research output is guaranteed by a rigorous peer review process. ESRI researchers are experts in their fields and are committed to producing work that meets the highest academic standards and practices.The work of the Institute is disseminated widely in books, journal articles and reports. ESRI publications are available to download, free of charge, from its website. Additionally, ESRI staff communicate research findings at regular conferences and seminars.The ESRI is a company limited by guarantee, answerable to its members and governed by a Council, comprising up to 14 members who represent a crosssection of ESRI members from academia, civil services, state agencies, businesses and civil society. The Institute receives an annual grant-in-aid from the Department of Public Expenditure and Reform to support the scientific and public interest elements of the Institute's activities; the grant accounted for an average of 30 per cent of the Institute's income over the lifetime of the last Research Strategy. The remaining funding comes from research programmes supported by government departments and agencies, public bodies and competitive research programmes.

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“…Rudkowsky et al (2017) study several machine learning approaches based on word embeddings for Austrian parliamentary speeches. Similarly, Abercrombie and Batista-Navarro (2020) and Elkink and Farrell (2021) investigate predicting votes based on the parliament speeches.…”

Section: Sentiment In Politicsmentioning

confidence: 99%

Multi-aspect Multilingual and Cross-lingual Parliamentary Speech Analysis

Miok¹,

Tenorio²,

Osenova³

et al. 2022

Preprint

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Parliamentary and legislative debate transcripts provide an exciting insight into elected politicians' opinions, positions, and policy preferences. They are interesting for political and social sciences as well as linguistics and natural language processing (NLP). Exiting research covers discussions within individual parliaments. In contrast, we apply advanced NLP methods to a joint and comparative analysis of six national parliaments (Bulgarian, Czech, French, Slovene, Spanish, and United Kingdom) between 2017 and 2020, whose transcripts are a part of the ParlaMint dataset collection. Using a uniform methodology, we analyze topics discussed, emotions, and sentiment. We assess if the age, gender, and political orientation of speakers can be detected from speeches. The results show some commonalities and many surprising differences among the analyzed countries.

show abstract

Predicting vote choice in the 2020 Irish general election

Cited by 16 publications

References 19 publications

Multi-aspect multilingual and cross-lingual parliamentary speech analysis

Multi-aspect multilingual and cross-lingual parliamentary speech analysis

Changing social and political attitudes in Ireland and Northern Ireland

Multi-aspect Multilingual and Cross-lingual Parliamentary Speech Analysis

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